WO2012159012A1 - Caractérisation de matières alimentaires par identification magnéto-optique - Google Patents

Caractérisation de matières alimentaires par identification magnéto-optique Download PDF

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Publication number
WO2012159012A1
WO2012159012A1 PCT/US2012/038534 US2012038534W WO2012159012A1 WO 2012159012 A1 WO2012159012 A1 WO 2012159012A1 US 2012038534 W US2012038534 W US 2012038534W WO 2012159012 A1 WO2012159012 A1 WO 2012159012A1
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WO
WIPO (PCT)
Prior art keywords
skin
light
food material
opto
spectral
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PCT/US2012/038534
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English (en)
Inventor
Sava Marinkovich
Djuro Koruga
Jadran Bandic
Lidija MATIJA
Rahul Mehendale
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Myskin, Inc.
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Application filed by Myskin, Inc. filed Critical Myskin, Inc.
Priority to GB1322584.2A priority Critical patent/GB2506542A/en
Publication of WO2012159012A1 publication Critical patent/WO2012159012A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/21—Polarisation-affecting properties
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/251—Colorimeters; Construction thereof
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/4738—Diffuse reflection, e.g. also for testing fluids, fibrous materials
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/4788—Diffraction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/55—Specular reflectivity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/02—Food
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N2021/178—Methods for obtaining spatial resolution of the property being measured
    • G01N2021/1782—In-depth resolution
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/94—Investigating contamination, e.g. dust
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/02—Mechanical
    • G01N2201/022—Casings
    • G01N2201/0221—Portable; cableless; compact; hand-held
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/06—Illumination; Optics
    • G01N2201/063—Illuminating optical parts
    • G01N2201/0634—Diffuse illumination

Definitions

  • This invention relates to the field of characterization and analysis of biological materials and more particularly, to the field of characterization and analysis of food materials.
  • teeth comprise of the following parts, namely enamel, dentin, cementum and pulp.
  • tooth enamel is the hardest and most highly mineralized substance of the body. Tooth enamel with dentin, cementum and dental pulp is one of the four major tissues, which make up the tooth in vertebrates. Ninety-six percent of enamel consists of mineral whereas the remaining four percent of enamel is composed of water and organic material. Normally, the color of enamel varies from light yellow to grayish white. However, at the edges of teeth the color of enamel sometimes has a slightly blue tone because there is no dentin underlying the enamel.
  • dentin is covered by enamel on the crown and cementum on the root and surrounds the entire pulp.
  • seventy percent of dentin consists of the mineral hydroxylapatite, twenty percent is organic material and ten percent is water. Yellow in appearance, it greatly affects the color of a tooth due to the translucency of enamel.
  • Dentin which is less mineralized and less brittle than enamel, is necessary for the support of enamel.
  • Primary dentin is the outermost layer of dentin and borders the enamel.
  • Secondary dentin is a layer of dentin produced after the root of the tooth is completely formed. Tertiary dentin is created in response to a stimulus, such as a carious attack.
  • Mineralized tissues are biological materials that incorporate minerals into soft matrices to get the stiffness needed for a protective shield or structural support in most cases.
  • mineralized tissues are found in bone, mollusc shells, deep sea sponge Euplectella species, radiolarians, diatoms, antler bone, tendon, cartilage, tooth enamel and dentin. These tissues have been finely tuned to enhance their mechanical capabilities over millions of years of evolution.
  • mineralized tissues have been the subject of many studies since there is a lot to learn from nature as seen from the growing field of biomimetics. The remarkable structural organization and engineering properties makes these tissues desirable candidates for duplication by artificial means. Mineralized tissues inspire miniaturization, adaptability and multifunctionality.
  • Mineralized tissues combine stiffness, low weight, strength and toughness due to the presence of minerals (the inorganic portion) in soft protein networks and tissues (the organic part).
  • minerals the inorganic portion
  • tissues the organic part
  • Two types of biological tissues have been the target of extensive investigation, namely nacre from seashells and bone that are both high performance natural composites.
  • Many mechanical and imaging techniques such as nanoindentation and Atomic Force Microscopy (or AFM), are used to characterize these tissues.
  • AFM Atomic Force Microscopy
  • dental caries also known as tooth decay or cavity, a disease wherein bacterial processes damage hard tooth structure, i.e. enamel, dentin, and cementum. These tissues progressively break down, producing dental caries (or cavities, holes in the teeth).
  • Two groups of bacteria are responsible for initiating caries: Streptococcus Mutans and Lactobacillus. If left untreated, the disease can lead to pain, tooth loss, infection, and, in severe cases, death.
  • caries remains one of the most common diseases throughout the world. Cariology is the study of dental caries.
  • Caries teeth decay
  • Caries teeth decay
  • the inadequacies of existing clinical tools are compounded by the fact that some dentists do not regularly assess patients for caries with x-rays owing to fears associated with exposure to ionizing radiation. These fears are even more acute when assessing children.
  • Dental caries and dental erosion are endemic in most of the world's population. Caries is a subsurface disease until the surface breaks down (cavitates) to produce an actual cavity in a tooth. Prior to surface cavitation, the carious lesion has the potential to be arrested or even remineralised.
  • Dental erosion i.e. the progressive loss of tooth substance from the surface
  • dental erosion is a growing problem, largely owing to an increased consumption of acid-containing beverages.
  • dental researchers have begun to look at technologies that might assist dentists in identifying and measuring dental caries and erosion.
  • primary diagnosis involves inspection of all visible tooth surfaces using a good light source, dental mirror and explorer.
  • dental radiographs X-rays
  • X-rays may show dental caries before it is otherwise visible, particularly caries between the teeth.
  • Large dental caries are often apparent to the naked eye, but smaller lesions can be difficult to identify.
  • Visual and tactile inspections along with radiographs are employed frequently among dentists, particularly to diagnose pit and fissure caries.
  • uncavitated caries is often diagnosed by blowing air across the suspect surface, which removes moisture and changes the optical properties of the unmineralized enamel.
  • an Opto- Magnetic method with enhanced qualitative and quantitative parameters, such as novel, early or premature detectability, practitioner capability, subjectivity or knowledge independent diagnosability, enhanced sensitivity, enhanced specificity, enhanced efficiency, greater accuracy, easily operable, rapid, economical, precise, timely and minute variation sensitive, for analysis of teeth based on Opto-Magnetic properties of light-matter interaction and systems and apparatuses thereof.
  • hydrogen bonds are often described as electrostatic dipole-dipole interactions. Specifically, as per advanced theory, hydrogen bonds are viewed as metric-dependent electrostatic scalar field between two or more intermolecular bonds.
  • intermolecular interactions are considered as intermolecular forces of attraction between two molecules or atoms. They occur from either momentary interactions between molecules, such as the London dispersion force or permanent electrostatic attractions between dipoles. However, they are also explained using a simple logical approach as in intermolecular forces, or using a quantum mechanical approach.
  • Bond distances and angles can be calculated as accurately as they can be measured (distances to a few pm and bond angles to a few degrees). For small molecules, calculations are sufficiently accurate to be useful for determining thermodynamic heats of formation and kinetic activation energy barriers.
  • Hydrogen bonds have dual property, such as classical (i.e. electrostatic interaction based on Coulomb's law) and quantum (i.e. wave function based on Schrodinger equation).
  • an Opto- Magnetic method with enhanced qualitative and quantitative parameters, such as novel, enhanced and easy interpretability, enhanced and easy detectability, enhanced sensitivity, enhanced specificity, enhanced efficiency, greater accuracy, easily operable, rapid, economical, precise, timely and minute variation sensitive, for analysis of water samples based on Opto-Magnetic properties of light-matter interaction and systems and apparatuses thereof.
  • bioimpedance is the response of a living organism to an externally applied electric current.
  • Bioimpedance is a measure of the opposition to the flow of the electric current through the tissues, which is the opposite of electrical conductivity.
  • This measurement of the bioimpedance (or bioelectrical impedance) of the humans and animals has proved as a useful noninvasive method for the computation of one or more physiological parameters, such as blood flow (often referred to as Bioimpedance Plethysmography) and body composition (known as Bioelectrical Impedance Analysis or BIA).
  • the impedance of skin is dominated by the stratum corneum at low frequencies.
  • skin impedance is determined mainly by the stratum corneum at frequencies below 10 kHz whereas by the viable skin at higher frequencies.
  • Skin impedance may certainly be dependent on one or more factors, such as skin hydration, dimensional and geometrical specifications of electrodes used thereof, and the like, but may nevertheless function as a rough guideline.
  • the Cole- Cole (Cole) equation has been found suitable for modeling most electrical measurements on biological tissue, including skin. However, the impact of the skin hydration by layers to bioelectrical properties is not fully tested.
  • Bioelectro-physical properties of human skin tissue like most other soft tissues, exhibit electroviscoelastic behavior.
  • it is also obligatory to capture and maintain (i.e. manage) experimental data over a wide range of time scales.
  • Bio-impedance can be measured by applying electricity from an external source outside the living organism. In order to analyze the skin impedance effectively, it is desirable to introduce the skin impedance model. Additionally, the complex modulus concept is a powerful and widely used tool for characterizing the electroviscoelastic behavior of materials in the frequency domain. In this case, according to the proposed concept, bioimpedance moduli can be regarded as complex quantities.
  • ageing or aging is the accumulation of changes in an organism or object over time.
  • ageing in humans refers to a multidimensional process of physical, psychological, and social change. Some dimensions of ageing grow and expand over time, while others decline. Reaction time, for example, may slow with age, while knowledge of world events and wisdom may expand. Research shows that even late in life potential exists for physical, mental, and social growth and development. Ageing is an important part of all human societies reflecting the biological changes that occur, but also reflecting cultural and societal conventions.
  • physiological aging is the combination of processes of deterioration, which follow the period of development of an organism.
  • physiological aging is the change in the biology of an organism as it ages after its maturity. Such changes range from those affecting its cells and their function to that of the whole organism.
  • organism senescence is the aging of whole organisms.
  • Blepharoplasty is a surgical procedure that can restore a youthful appearance to the eye area.
  • the upper and lower eyelids are lifted and loose or excess skin and fat tissue are removed from the eye area.
  • the procedure is limited to the eyelids and may be combined with methods to improve other areas of the face. Brow lifts, which raise the eyebrows or keep them from sagging over the eyes, may be recommended to help improve the upper third of the face.
  • Botulinum Toxin Therapy is another solution. Before treatment, the dermatologist obtains the patient's medical history, including any medications taken. Treatment involves injecting very small amounts of Botulinum toxin directly into the underlying facial muscles to relax them. A tiny needle is used; the procedure is well tolerated and takes just a few minutes with no "down time” or prolonged recovery period.
  • an Opto-Magnetic method with enhanced qualitative and quantitative parameters, such as novel, enhanced and easy interpretability, enhanced and easy detectability, enhanced sensitivity, enhanced specificity, enhanced efficiency, greater accuracy, easily operable, rapid, highly interactive, fuzzy logic knowledge-based, artificial neural network knowledge-based, economical, precise, timely and minute variation sensitive, for analysis of skin based on Opto-Magnetic properties of light-matter interaction and systems and apparatuses thereof.
  • an Opto-Magnetic method with enhanced qualitative and quantitative parameters, such as novel, enhanced and easy interpretability, enhanced and easy detectability, enhanced sensitivity, enhanced specificity, enhanced efficiency, greater accuracy, easily operable, rapid, highly interactive, fuzzy logic knowledge-based, artificial neural network knowledge-based, economical, precise, timely and minute variation sensitive single handed operability, motion tolerant, skin-based inductive chargeability, lens-independent (or -free), reduced complexity or simplicity, economical, disease diagnosability, rapid drug screenability or high throughput screenability, easy integrability or couplability to portable communication devices and slim configuration, for imaging and analysis of skin based on Opto-Magnetic properties of light-matter interaction and systems and apparatuses thereof.
  • enhanced qualitative and quantitative parameters such as novel, enhanced and easy interpretability, enhanced and easy detectability, enhanced sensitivity, enhanced specificity, enhanced efficiency, greater accuracy, easily operable, rapid, highly interactive, fuzzy logic knowledge-based, artificial neural network knowledge-based, economical, precise, timely and minute variation sensitive single handed operability, motion tolerant, skin-based inductive charge
  • skin is made up of three main different skin layers, namely epidermis, dermis and subcutis.
  • the epidermis is tightly connected to the dermis by a basement membrane.
  • the basement membrane is very thin layer between the epidermis and dermis.
  • the basement membrane structurally and energetically separates the epidermis and the dermis.
  • the thickness of epidermis is approximately 200 ⁇ .
  • the thickness of epidermis varies and is up to approximately 2 mm, depending on the location on the body. Still, however, the thickness of the epidermis varies according to the volume of the water held thereof.
  • the epidermis is divided into five sub layers, namely stratum corneum (or horny cell layer), stratum lucidum (or clear layer), stratum granulosum (or granular layer), stratum spinosum (or prickle cell layer) and stratum basale (or basal cell layer).
  • stratum corneum or horny cell layer
  • stratum lucidum or clear layer
  • stratum granulosum or granular layer
  • stratum spinosum or prickle cell layer
  • stratum basale stratum basale
  • keratinocytes are produced in the stratum basale, which holds approximately 10% of the epidermal water. With aging, this layer becomes thinner and losses the ability to retain water. Basal cells, through the process of turn-over, make their shape somewhat flatter and form stratum spinosum layer with about 20 layers that lie on the top of the basal cell layer. The thickness of the stratum spinosum layer ranges from a minimum of approximately 60 ⁇ to a maximum of approximately 150 ⁇ , and holds about 35% of epidermal water. In the next turnover process organelles, such as nuclei and mitochondria, start to resolve. Cells are increasingly filled with keratin fibers and contain less intracellular water than basal and spinosum cells. However, this layer called stratum granulosum, is about 5 ⁇ thick and has very well ordered lipid-water layers, from 5 to 20, depending on the skin condition. Water layers are thin from 20 to 50 nm.
  • the skin is usually observed as a simple structure with equivalent electrical model, which includes general properties of epidermis, basal membrane and dermis. Further, there are numerous conventional approaches to skin characterization. However, the emerging technologies have been mainly focused on non-invasive methods in order to limit pain to patients. Lines of investigations cover aspect related to dermatology or dermocosmetic science by exploiting characteristic measurements related to one or more properties of the skin, such as mechanical, electrical, thermal, optical, acoustic, piezoelectric and morphological.
  • an Opto-Magnetic method with enhanced qualitative and quantitative parameters, such as novel, easily operable, rapid, economical, precise, timely and minute variation sensitive, complex analytical capability, nanomaterials detectability and analyzability and dual process approach, for characterization of skin samples based on Opto-Magnetic properties of light-matter interaction and systems and apparatuses thereof.
  • Food testing is an important means of assuring that the food sold to the public does not cause any damage to any person's health. There are a variety of food safety issues that need to be addressed in an efficient, effective, and convenient manner.
  • the problem of generating a skin condition assessment in real-time is solved by having a skin condition analysis module capable of doing real-time analysis of digital skin data, acquired partly using diffused reflectance spectroscopy and/ or detecting the red-green-blue components of re-emitted white light.
  • a skin care device may include an electromagnetic radiation source capable of directing incident electromagnetic radiation to a location on the skin of a user, a radiation detector for measuring various parameters of radiation re-emitted from the location, and a skin condition analysis module coupled to the detector, the analysis module capable of generating a skin condition assessment in real-time, based partly on at least one of RGB analysis and diffused reflectance analysis of the radiation parameters.
  • the incident electromagnetic radiation may include radiation in at least one of the visible, near-infrared, and near-ultraviolet spectrum.
  • the incident radiation may include white light.
  • the radiation parameters may include at least the degree of polarization of the re-emitted radiation.
  • the radiation source may be a set of light emitting diodes.
  • the skin condition assessment may also be partly based on analysis of a photographic image of a skin region surrounding the location.
  • the device may be a miniature device. Miniature may mean that no dimension of the detector exceeds six inches.
  • the device may further comprise a memory module for storing the skin condition assessment.
  • the device may further comprise a user interface. The user interface may be operated using voice commands.
  • skin assessment data of locations may be overlaid on an image of a larger skin region and displayed on the display surface.
  • the device may further comprise an access restriction module used for restricting access to authorized users only. The access restriction module may be based on biometric access control.
  • the device may be capable of generating alerts about abnormal skin conditions in real-time.
  • the device may further comprise a skin care regimen recommendation module that generates a displayable skin care regimen recommendation.
  • the skin care regimen recommendation may be based at least partly on determination of a skin profile of the user and use of skin care regimen recommendations of persons with a similar profile.
  • the skin care regimen recommendation module may be linked to a product database.
  • the product database may include products available in a point-of-sale location.
  • the availability of a specific product recommended by the skin care regimen recommendation module may be indicated by an audio-visual signal.
  • the device may further comprise a skin care regimen effectiveness module that generates a displayable skin care regimen effectiveness report.
  • the device may further comprise a communication module for communicating with a remote computer.
  • the communication may occur wirelessly.
  • the communication may occur over an internet.
  • the remote computer may be operable by a physician.
  • the device may be wand-shaped.
  • the device may be wearable by the user.
  • the skin care device may include an electromagnetic radiation source capable of directing incident electromagnetic radiation to a location on the skin of a user, a detector for measuring various parameters of radiation re-emitted from the location, a skin condition analysis module coupled to the detector, the analysis module capable of generating a skin condition assessment in real-time, based partly on at least one of RGB analysis and diffused reflectance analysis of the radiation parameters, and a display panel for reflecting the image of the user.
  • the display panel may be touch-sensitive such that touching the location in a skin region image displayed in the display panel triggers display of a magnified image of the location.
  • the device may further comprise a camera.
  • the camera may be integral with the display panel.
  • the camera may be wirelessly linked to the display panel.
  • the display panel may be a mirror.
  • a stored image of the user is used to automatically identify the person.
  • the device may further comprise a user interface for controlling the skin care device.
  • the user interface may be operated using voice commands.
  • the device may further comprise a skin care regimen recommendation module capable of generating a displayable skin care regimen recommendation.
  • the skin care regimen recommendation may be based at least partly on determination of a skin profile of the user and use of skin care regimen recommendations of persons with a similar profile.
  • the device may further comprise a skin care regimen effectiveness module capable of generating a displayable skin care regimen effectiveness report.
  • an imaging device permits a user to take high magnification pictures of the skin in the vicinity of an area of concern and submit those pictures, optionally along with textual and data responses, for medical, non-medical, and cosmetic analysis, diagnosis and treatment recommendation and follow-up.
  • a method and system of a non-invasive imaging device may comprise an illumination source comprising an incident light source to direct light upon skin; and a detector for detecting the degree of polarization of light reflected from the skin.
  • the illumination source may be positioned to direct light at a selected angle alpha. Varying alpha may vary the depth of the measurement of the layers in the skin. Each depth may have a specific angle which produces a full polarized reflection.
  • the incident light source may be an unpolarized light source. The unpolarized light may be white light, multiple selected wavelengths, or a single wavelength.
  • the method and system may further comprise a sensor for capturing an image of the reflected or re-emitted light.
  • the method and system may further comprise an optical facility for detecting reflected or re-emitted light from the skin.
  • the method may determine both reflected or re-emitted light, and newly emitted light, through the process of absorption and re-emission.
  • the method and system may further comprise a communication facility for transmitting the detected information.
  • the method and system may further comprise a storage facility for storing information collected by the device.
  • a method and system for determining a skin state may comprise illuminating skin with an incident light source, detecting the degree of polarization of light reflected from the skin, and determining a skin state based on an aspect of the polarization of the reflected or re-emitted light.
  • the incident light may be directed at a selected angle alpha. Varying alpha may vary the depth of the measurement of the layers in the skin. Each depth may have a specific angle which produces a full polarized reflection.
  • the incident light source may be an unpolarized light source. The unpolarized light may be white light, multiple selected wavelengths, or a single wavelength.
  • the aspect of the polarization may be at least one of an orientation, an amplitude, a phase, an angle, a shape, a degree, an amount, and the like.
  • determining may be done using an algorithm.
  • the algorithm may involve artificial neural networks, non-linear regression, genetic algorithms, fuzzy logic, fractal and multi-fractal analysis, and the like.
  • the methods and systems may further comprise filtering the reflected or re-emitted light to obtain polarized light of at least one wavelength defined by the filter output.
  • the algorithmic analysis may be performed on the filtered image.
  • determining may involve creating an image from the difference between the reflected diffusion light and the reflected polarized light.
  • determining may involve comparing the aspect of the polarization of the reflected or re- emitted light to a calibration signal.
  • determining may further comprise considering at least one of user input and a visual analysis.
  • a non-invasive imaging device may comprise an illumination source comprising an incident light source to direct light upon an area of concern and a detector for detecting the degree of polarization of light reflected from the area of concern.
  • the illumination source may be positioned to direct light at a selected angle alpha. Varying alpha may vary the depth of the measurement of the layers in the skin. Each depth may have a specific angle which produces a full polarized reflection.
  • the incident light source may be an unpolarized light source. The unpolarized light may be white light, multiple selected wavelengths, or a single wavelength.
  • the method and system may further comprise a sensor for capturing an image of the reflected or re-emitted light.
  • the method and system may further comprise an optical facility for detecting reflected or re-emitted light from the skin.
  • the method and system may further comprise a communication facility for transmitting the detected information.
  • the method and system may further comprise a storage facility for storing information collected by the device.
  • a method of determining moisture levels in the skin may comprise emitting incident light towards a skin structure, detecting a degree of polarization of the light induced by the skin structure, and determining a moisture level based on the amount of polarized and reflected or re- emitted light.
  • the method and system may further comprise combining the assessment of moisture level with skin color measurements to determine luminosity.
  • the incident light may be unpolarized light.
  • the unpolarized light may be white light, light of multiple selected wavelengths, or of a single wavelength, or one or more monochromatic lights.
  • determining may involve use of an algorithm.
  • determining a moisture level may be based on the ratio of polarized and reflected or re-emitted light.
  • a method and system of determining elasticity of the skin may comprise emitting incident light towards a skin structure, detecting an aspect of polarization of the light reflected by the skin structure, correlating the aspect of polarization with a concentration of elastin, and determining elasticity level based on the elastin status.
  • determining may involve use of an algorithm.
  • the incident light may be unpolarized light.
  • the unpolarized light may be white light, light of multiple selected wavelengths, or a single wavelength of light.
  • a method and system of determining firmness of the skin may comprise emitting incident light towards a skin structure, detecting an aspect of polarization of the light reflected by the skin structure, correlating the aspect of polarization with the status of at least one of an elastin, a collagen, and an activity of a sebaceous gland, and determining firmness based on the concentration of at least one of elastin and collagen and sebaceous gland activity.
  • the sebaceous gland activity may be indicated by at least one of a number of glands, percent of glands open/closed, and level of clog/ fill.
  • correlating may involve use of an algorithm.
  • a method and system for obtaining dermal biophysical properties may comprise performing a spectral analysis of image data acquired from the degree of polarization of reflections and absorption and re-emission of incident light from skin structures, wherein the property is at least one of a structure, form, status, number, size, state, and stage of at least one of a: melanocyte, melanin, hemoglobin, porphyrin, tryptophan, NADH, FAD, keratin, carotene, collagen, elastin, sebum, sebaceous gland activity, pore (sweat and sebaceous), moisture level, elasticity, luminosity, firmness, fine line, wrinkle count and stage, pore size, percent of open pores, skin elasticity, skin tension line, spot, skin color, psoriasis, allergy, red area, general skin disorder or infection, tumor, sunburn, rash, scratch, pimple, acne, strias, insect bite, itch, bleeding, injury,
  • a system and method may comprise providing an interface that includes a social networking domain or rating-and-ranking system and at least one of a skin state determination facility and a recommendation engine, and enabling users, either all or a selected few, of the interface to perform a skin state determination within the interface.
  • the skin state determination facility may comprise capturing images with a non-invasive imaging device comprising an illumination source comprising an incident light source to direct light upon skin, and a detector for detecting the degree of polarization of light reflected from the skin, and determining a skin state based on an aspect of the polarization of the reflected or re-emitted light.
  • the method and system may further comprise receiving product and regimen recommendations from the recommendation engine based on what other users with similar skin states are using as well as data regarding ingredients, effectiveness, safety, and the like.
  • the method and system may further comprise comparing skin states, products, regimens, and recommended products or regimens with peers within the social networking domain of the interface. Comparing may comprise an analysis of similarity based on the spectral analysis of the degree of polarization of reflected or re-emitted light from users' skin.
  • the interface may comprise a regimen tracker.
  • the regimen tracker may be populated using a drag-and- drop or click-to-add functionality.
  • the interface may comprise a rating facility or a product information facility.
  • the product information facility may enable a user to obtain product information by search. Search may be a search of product identifiers, product ratings, drag-and-drop items, images, barcode scans, skin states, and profiles.
  • a method and system for determining a skin state may comprise obtaining the answers to a series of subjective questions regarding the skin, obtaining an objective skin analysis using a dermal imaging device, and combining the subjective and objective results algorithmically to obtain a skin state.
  • a system and method for providing recommendations for skin care based on a skin state and a skin care goal may comprise obtaining a skin state of an individual, categorizing the individual by skin state, and recommending products and regimens that are effective for other individuals of the category in achieving the skin care goal.
  • the system may be operable over a network.
  • the skin state may be determined based on analysis of the degree of polarization of light reflected from the skin of the individual.
  • a method for tracking the effectiveness of a skin care product or regimen may comprise obtaining a baseline skin state assessment, recommending a monitoring interval based on at least one of the skin care goal, product, and regimen, obtaining a second skin state assessment, comparing the second assessment to the baseline assessment to determine progress towards a skin care goal, and optionally, optimizing the regimen or product in order to improve a skin state.
  • the skin assessment may be based on analysis of the degree of polarization of light reflected from the skin of the individual.
  • a personalized skin condition analysis system and related methods may comprise an imaging device, comprising an illumination source comprising an incident light source to direct light upon skin, and a detector for detecting the degree of polarization of light reflected from the skin, and a user interface for controlling the device.
  • the device may be adapted to interact with a physical interface to download image data to update a record of at least one of a practitioner, a spa, a salon, cosmetic sales, a cosmetics manufacturer, a clinical trials database, and a third party database.
  • the illumination source may be positioned to direct light at a selected angle alpha. Varying alpha may vary the depth of the measurement of the layers in the skin.
  • the incident light source may be an unpolarized light source.
  • the unpolarized light may be white light, multiple selected wavelengths, or a single wavelength.
  • the method and system may further comprise a sensor for capturing an image of the reflected or re-emitted light.
  • the method and system may further comprise an optical facility for detecting reflected or re-emitted light from the skin.
  • the method and system may further comprise a communication facility for transmitting the detected information.
  • the method and system may further comprise a storage facility for storing information collected by the device.
  • a non-invasive imaging device may comprise an illumination source comprising an incident light source to direct light upon skin; and a detector for detecting a characteristic of the light reflected from the skin.
  • the illumination source may be positioned to direct light at a selected angle alpha. Varying alpha may vary the depth of the measurement of the layers in the skin. Each depth may have a specific angle which produces a full polarized reflection.
  • the incident light source may be a polarized light source or unpolarized light source. The unpolarized light may be at least one of white light, light of a single wavelength, and light of multiple single wavelengths.
  • the device may further comprise a sensor for capturing an image of the reflected or re-emitted light.
  • the device may further comprise an optical facility for detecting reflected or re-emitted light from the skin.
  • the device may further comprise a communication facility for transmitting the detected information.
  • the device may further comprise a storage facility for storing information collected by the device.
  • the reflected or re-emitted light may be at least one of polarized light and unpolarized light.
  • a method and system for determining a skin state may comprise illuminating skin with an incident light source; detecting a characteristic of the light reflected from the skin; and determining a skin state based on at least one characteristic of the reflected or re-emitted light.
  • the incident light may be directed at a selected angle alpha. Varying alpha may vary the depth of the measurement of the layers in the skin. Each depth may have a specific angle which produces a full polarized reflection.
  • the incident light may be unpolarized or polarized light. The unpolarized light may be at least one of white light, light of a single wavelength, and light of multiple single wavelengths.
  • the reflected or re-emitted light may be at least one of polarized light and unpolarized light.
  • the characteristic may be at least one of light source, light intensity, wavelength of light, angle of light, electrical and magnetic properties of the light, and polarization state of the light.
  • An aspect of the polarization may be at least one of an orientation, an amplitude, a phase, an angle, a shape, a degree, and an amount.
  • determining may be done using an algorithm.
  • the algorithm may involve artificial neural networks, non-linear regression, genetic algorithms, fuzzy logic, or fractal and multi-fractal analysis.
  • the method and system may further comprise filtering the reflected or re-emitted light to obtain light of a wavelength defined by the filter output.
  • the analysis may be performed on the filtered image.
  • determining may involve creating an image of the difference between reflected diffusion light and reflected polarized light.
  • determining may involve comparing the aspect of the polarization of the reflected or re-emitted light to a calibration signal.
  • determining may further comprise considering at least one of user input and a visual analysis.
  • a non-invasive imaging device may comprise an illumination source comprising an incident light source to direct light upon an area of concern; and a detector for detecting a characteristic of the light reflected from the area of concern.
  • the illumination source may be positioned to direct light at a selected angle alpha. Varying alpha may vary the depth of the measurement of the layers in the skin. Each depth may have a specific angle which produces a full polarized reflection.
  • the incident light source may be a polarized light source or unpolarized light source. The unpolarized light may be at least one of white light, light of a single wavelength, and light of multiple single wavelengths.
  • the device may further comprise a sensor for capturing an image of the reflected or re- emitted light.
  • the device may further comprise an optical facility for detecting reflected or re-emitted light from the skin.
  • the device may further comprise a communication facility for transmitting the detected information.
  • the device may further comprise a storage facility for storing information collected by the device.
  • the reflected or re-emitted light may be at least one of polarized light and unpolarized light.
  • a system and method may be used to determine healthy and melanocytic skin.
  • the first reflected spectrum and/or emission spectrum from sample which is skin malformation (SM), subtract reflected spectrum from normal healthy skin (SN).
  • the second from obtained resulting spectral plots (SM - SN) subtract reflected spectrum from adequate comparing screen, which represents spectral plot of the light source (SO).
  • SO light source
  • a system and method may comprise capturing an image of a material illuminated with incident non-angled white light and angled white light, generating a normalized red and blue color channel histogram for each image, correlating the normalized red and blue color channel histograms to a wavelength scale to obtain red and blue color channel spectral plots, and convoluting the spectral plots by subtracting the spectral plot for angled light from the spectral plot for non- angled light for each color channel to generate red and blue normalized, composite color channel spectral plots, and subtracting the normalized, composite blue channel spectral plot from the normalized, composite red channel spectral plot to generate a spectral signature for the material.
  • the illumination source may be positioned to direct light at a selected angle alpha. Varying alpha varies the depth of the measurement in the material.
  • the unit scale on the spectral signature may be a difference of wavelength.
  • the material is inorganic and/ or organic matter.
  • the spectral signature may be analyzed for at least one of number of peaks and troughs, amplitude and shape of peaks and intermediate structures and patterns.
  • the spectral signature may be analyzed for metal composition, identification, purity, and strength.
  • the spectral signature may be analyzed for water quality, composition, and purity.
  • elements of the spectral signature may be tagged and tracked over time in order to track changes in the characteristics of the material.
  • the spectral signature may be analyzed to measure, track or monitor a skin state.
  • the spectral signature may be useful for the counterfeit analysis of money.
  • the spectral signature may be analyzed for at least one of sweat gland activity and anti-perspirant effectiveness.
  • the spectral signature may be analyzed for Mad Cow disease.
  • the spectral signature may be analyzed for food, all epidermal diseases, melanoma and skin cancers, rheumatoid diseases, and all diseases that show on the skin.
  • the spectral signature may be useful for monitoring post-operative cosmetic concerns.
  • the spectral signature may be useful for predicting and monitoring secretion from the mammary glands of lactating women.
  • the spectral signature may be fed into a recommendation engine to provide feedback and modifications to aspects of a regimen.
  • the wavelength position of ideal blue in Maxwell's color triangle is aligned with the wavelength position of ideal red in Maxwell's color triangle when convoluting the composite spectral plots to obtain the spectral signature.
  • a method for determining skin characteristics and cosmetic features using color analysis may include a step of analyzing color of skin images in a pixel by pixel manner in a Red Green Blue (RGB) color system for an acquired digital image.
  • the step of analyzing color of skin images in a pixel by pixel manner in a RGB color system for an acquired digital image may include analyzing a picture of a part of a person's skin by generating a table of most frequent colors appearing in the picture.
  • a method for determining skin characteristics and cosmetic features using color analysis includes a step of generating a sample of most frequent standard RGB (sRGB) colors responsive to analyzing color of skin images in a pixel by pixel manner in the RGB color system for the acquired digital image after converting colors obtained in device dependent RGB color system into device independent standard RGB color system (sRGB).
  • the step of generating a sample of most frequent sRGB colors responsive to analyzing color of skin images in the sRGB color system for the acquired digital image may include preserving a plurality of sRGB color values.
  • the sRGB color system may be used for image analysis. Determination of other skin characteristics, melanoma, skin related tumors and skin related disorders require image analysis based on other color systems such as YIQ, YCbCr, L * a * b * , L * u * v * and HSL/HSV.
  • the enhancement of the current algorithm may include at least one of these color systems and its/their correlation with presented sRGB analysis.
  • a method for determining skin characteristics and cosmetic features using color analysis includes a step of modeling the R, G and B component color distribution with Gaussian probabilistic distribution with estimated parameters (expected value and standard deviation) on the generated sRGB color sample for the acquired digital image further including approximating colors on the generated sRGB color samples by a Gaussian normal distribution.
  • the step of approximating colors on the generated sRGB color samples by a Gaussian normal distribution comprises approximating colors on the generated sRGB color samples by a superposition of a plurality of Gaussian normal distributions.
  • a method for determining skin characteristics and cosmetic features using color analysis includes a step of generating a phototype of the skin through a decision tree unit responsive to the estimated distribution model parameters colors.
  • the phototype of the skin may be generated according to a corrected Fitzpatrick classification.
  • the step of generating phototype of the skin according to corrected Fitzpatrick classification includes generating phototype of the skin according to a skin type scale which ranges from very fair skin to very dark skin. This method may be measured both on the most exposed region and relate to the current level of phototype based on level of tan on the skin.
  • a system for skin phototype determination using photograph analysis may be disclosed.
  • the system may include an image capturing device for capturing digital images of a skin.
  • the image capturing device may include a digital camera unit.
  • the system for skin phototype determination using photograph analysis may include an analyzer coupled to the image capturing device for performing a pixel by pixel analysis of a picture of a part of a person's skin.
  • the analyzer may include a quantization device for generating a look-up table of most frequent colors appearing on the picture of the part of the person's skin.
  • the system for skin phototype determination using photograph analysis may include a sampling device coupled to the image capturing device for generating standard Red Green Blue (sRGB) color samples for the captured digital image of the skin.
  • sRGB standard Red Green Blue
  • the system for skin phototype determination using photograph analysis may include an approximating device coupled to the sampling device for approximating the color distribution parameters on the generated sRGB color samples using the estimates of expected value and standard deviation for the captured digital image of the skin.
  • the approximating device may include at least one Gaussian normal distribution unit.
  • the system for skin phototype determination using photograph analysis may include a decision tree unit coupled to the approximating device for generating a phototype of the skin using Red and Blue components of the approximated colors.
  • the decision tree unit may include a Fitzpatrick scaling unit for categorizing a skin phototype in accordance with a skin type scale which ranges from very fair skin to very dark skin.
  • an exemplary embodiment of the present invention discloses a scaled Gaussian normal distribution unit for approximating colors on the generated sRGB color samples using estimates of expected value and standard deviation for the captured digital image of the skin.
  • the system for skin phototype determination using photograph analysis may include a subsystem for determination of cosmetic features for a human element and a veterinary element.
  • the cosmetic features may further include features pertaining to hair, nail and skin.
  • the system may include a sampling device for generating standard Red Green Blue color samples of the captured digital image of the skin, the generated samples of standard Red Green Blue are in the range of values between 0 and 255 and they are preserved for further processing.
  • the system may include an approximating device coupled to the sampling device for approximating the color distribution parameters on the generated sRGB color samples in the range of values between 0 and 255 by Gaussian normal distribution using the estimates of expected value and standard deviation for the captured digital image of the skin.
  • system may further include a decision tree unit coupled to the approximating device for generating a phototype of the skin using standard Red and Blue components of the approximated colors, the decision tree unit with an algorithm equates estimates of expected values and standard deviation for the captured image of the skin to the Fitzpatrick notation of skin analysis for determination of skin phototype.
  • system may automatically adjust lighting intensity and wavelengths and angles in order to assess various factors of the skin.
  • skin phototype may be determined using photograph analysis for use in cosmetics and surgical industry.
  • a skin care device may include an electromagnetic radiation source capable of directing incident electromagnetic radiation to a location on the skin of a user, a radiation detector for measuring various parameters of radiation re-emitted from the location, and a skin condition analysis module coupled to the detector, the analysis module capable of generating a skin condition assessment in real-time, based partly on at least one of RGB analysis and diffused reflectance analysis of the radiation parameters.
  • incident electromagnetic radiation may include radiation in at least one of the visible, near-infrared, and near-ultraviolet spectrum.
  • the incident radiation may be white light.
  • the radiation parameters include at least the degree of polarization of the re-emitted radiation.
  • the radiation source may be a set of light emitting diodes.
  • the skin condition assessment may be also partly based on analysis of a photographic image of a skin region surrounding the location.
  • the device may be a miniature device. Miniature may mean that no dimension of the detector exceeds six inches.
  • the device may further include a memory module for storing the skin condition assessment.
  • the device may further include a user interface.
  • the device may further include a display surface.
  • the skin assessment data of locations may be overlaid on an image of a larger skin region and displayed on the display surface.
  • the device may further include an access restriction module used for restricting access to authorized users only.
  • the access restriction module may be based on biometric access control.
  • the device may be capable of generating alerts about abnormal skin conditions in real-time.
  • the user interface may be operated using voice and/or eye movement commands.
  • the device may further include a skin care regimen recommendation module that generates a displayable skin care regimen recommendation.
  • the skin care regimen recommendation may be based at least partly on determination of a skin profile of the user and use of skin care regimen recommendations of persons with a similar profile.
  • the skin care regimen recommendation module may be linked to a product database.
  • the product database may include products available in a point-of-sale location. The availability of a specific product recommended by the skin care regimen recommendation module may be indicated by an audio-visual signal.
  • the device may further include a skin care regimen effectiveness module that generates a displayable skin care regimen effectiveness report.
  • the device may further include a communication module for communicating with a remote computer.
  • the communication may occur wirelessly.
  • the communication may occur over an internet.
  • the remote computer may be operable by a physician.
  • the device may be wand-shaped.
  • the device may be wearable by the user.
  • the device an electromagnetic radiation source capable of directing incident electromagnetic radiation to a location on the skin of a user, a detector for measuring various parameters of radiation re-emitted from the location, a skin condition analysis module coupled to the detector, the analysis module capable of generating a skin condition assessment in real-time, based partly on at least one of RGB analysis and diffused reflectance analysis of the radiation parameters, and a display panel for reflecting the image of the user.
  • the display panel may be touch-sensitive such that touching the location in a skin region image displayed in the display panel triggers display of a magnified image of the location.
  • the skin care device may further include a camera.
  • the camera may be integral with the display panel.
  • the camera may be wirelessly linked to the display panel.
  • the display panel may be a mirror.
  • a stored image of the user may be used to automatically identify the person.
  • the device may further include a user interface for controlling the skin care device.
  • the user interface may be operated using voice and/or eye movement commands.
  • the device may further include a skin care regimen recommendation module capable of generating a displayable skin care regimen recommendation.
  • the skin care regimen recommendation may be based at least partly on determination of a skin profile of the user and use of skin care regimen recommendations of persons with a similar profile.
  • the device may further include a skin care regimen effectiveness module capable of generating a displayable skin care regimen effectiveness report.
  • a system and method for moving information objects available on a website to a receptacle to communicate with a plurality of people in a controlled access community network may include enabling movement of a plurality of information objects from a predetermined website to a web based network responsive to a regimen of a person, a routine of a person, a purpose of use of an information object of the plurality of information objects and a degree of affinity of a first person towards a second person, initiating at least one customized action from the actions including a drop down movement; a drag and drop movement for populating data; and a pop-up movement in a Graphical User Interface (GUI) responsive to enabling movement of a plurality of information objects from a predetermined healthcare website, and enabling transportation of the plurality of information objects across a plurality of websites.
  • GUI Graphical User Interface
  • the plurality of information objects may pertain to a questionnaire on at least one of a human skin condition, product information, an article, a blog posting, an image, a video, an individual message, a forum posting, and a veterinary skin condition.
  • the plurality of information objects pertains to a questionnaire on human cosmetic parameters and veterinary cosmetic parameters.
  • the questionnaire on human cosmetic parameters and veterinary cosmetic parameters may include questions on at least one of a human nail and a veterinary nail.
  • the questionnaire on human cosmetic parameters and veterinary cosmetic parameters may include questions on at least one of a human hair and a veterinary hair.
  • the purpose of use of the information object may pertain to controlling at least one of cleansing, protection, repair, moisturizing, elasticity, firmness, glow, luminosity, anti-inflammatory properties, anti-itch properties, anti- wrinkle properties, firming, exfoliating, anti-redness properties, oil controlling, anti-aging properties and shine of a human skin.
  • the degree of affinity of a first person towards a second person comprises at least one of a relationship of friendship between the first person and the second person; a genetic similarity between the first person and the second person; a similarity of lifestyle between the first person and the second person; a climatic similarity between a first residential environment and a second residential environment; and a skin type similarity between the first person and the second person.
  • the step of enabling transportation of the plurality of information objects across a plurality of websites may include a sub-step of dragging an item of user interest off a website of the plurality of websites in a predetermined format and transferring through an electronic signal to affiliates of a user accessing the website.
  • the affiliates of the user may be friends and relatives of the user or associated experts.
  • the step of enabling movement of a plurality of information objects from a predetermined website to a web based network may include a sub-step of enabling drop down menus on the Graphical User Interface (GUI) responsive to a plurality of end user convenience and requirement parameters.
  • GUI Graphical User Interface
  • the plurality of people in a web based network includes a plurality of people in an online friendship network.
  • the plurality of people in a web based network includes a plurality of people in an online social network.
  • an interface including a social networking domain and at least one skin health assessment and recommendation unit for enabling users of the interface to perform a skin health assessment within the interface and to receive product and regimen recommendations from a recommendation engine based on a predetermined usage of health assessment and maintenance data may include a regimen tracker populated using a drag and drop facility, a rating unit for rating a plurality of healthcare facilities, and a product information unit for enabling a user to obtain product information by conducting a web based search of a plurality of web based drag and drop products, web based images and bar code scans.
  • the regimen tracker includes a diet tracking unit.
  • the plurality of healthcare facilities comprises at least one of skin cleansing, skin protection, skin moisture control, skin repair, skin elasticity, skin luminosity, skin firmness, skin wrinkles, pore size on skin, spots on skin , glow on skin, hair color, hair type, age and life stage further including marriage, pregnancy, dating and social life.
  • the product information comprises at least one of a product type, a product function, a product format, a product appropriateness level, a regimen information, product articles, product blogs, product safety, product toxicity, a product effectiveness index, a product cost information, and a product timeliness information.
  • the interface is a multiple language and customized interface for: web based applications; mobile phone applications; touch screen applications; and personal digital assistant applications.
  • the interface is seamlessly coupled with a dermal imaging device for customized web based access, control and maintenance of spectral analysis of image data acquired from a degree of polarization of reflections and re-emission of incident light from skin structures.
  • the degree of polarization of reflections and/or re-emissions of incident light from skin structures is derived from at least one of a Red Green Blue (RGB) color analysis of a plurality of digital images; and an analysis from spectroscopic data image analysis.
  • RGB Red Green Blue
  • a system and method for determining a health state may include obtaining the answers to a series of subjective questions regarding health conditions, obtaining an objective health assessment report through a dermal imaging device, and generating a combination of answers to the series of subjective questions and the objective health assessment report to thereby generate a health state output and a real skin type output.
  • a real skin type output is generated based on biophysical properties generated by at least one of a person seeking skin health monitoring, a spa, and a cosmetic advisor.
  • the objective health assessment report may include an objective skin health assessment report on at least one of systemic hydration, skin hydration, skin firmness, skin wrinkles, pore size on skin, spots on skin, glow on skin, melanocyte, melanin, hemoglobin, porphyrin, tryptophan, NADH, FAH, keratin, carotene, collagen, elastin, sebum, sebaceous gland activity, sweat pore, sebaceous pore, moisture level, elasticity, luminosity, firmness, fine line, wrinkle count, pore size, percent of open pores, skin elasticity, skin tension line, spots, viscosity, epidermal, dermal sebum levels, skin color, psoriasis, allergy, red area, general skin disorder, infection, tumor, sunburn, rash, scratch, pimple, acne, insect bite, itch, bleeding, injury, inflammation, photodamage, pigmentation, tone, tattoo, percent burn, burn classification, mole, aspect of a skin lesion,
  • the objective health assessment report is sent to an end user through at least one of email, SMS, MMS, mobile phone, a graphical user interface (GUI) of an internet connected device, and a touch screen enabled personal digital assistant.
  • the system and method may further include obtaining health assessment and maintenance data from a physiologically polarized light data.
  • the step of obtaining health assessment and maintenance data from a physiologically polarized light data comprises obtaining health assessment and maintenance data from a Red Green Blue (RGB) color analysis device, wherein the data comprise at least one of a white light data, a blue light data, and an ultra violet light data.
  • RGB Red Green Blue
  • the step may further comprise obtaining at least one of the white light data, the blue light data, and the ultra violet light data by reading and recording conditions of at least one of the dermis and epidermis.
  • Obtaining health assessment and maintenance data from a physiologically polarized light data comprises obtaining data pertaining to age, geography and demography for a person subjected to health monitoring.
  • a web-enabled health tracking method and system may include a camera comprising a photo guide unit for generating notes for each photograph captured, an interface coupled between the camera and a web-enabled computing system for uploading the photograph captured by the camera, a graphical user interface unit included in the web-enabled computing system for generating a frequently asked questionnaire unit further comprising a self answer guide module, a scoring module coupled to the frequently asked questionnaire unit, a comparison module coupled to the scoring module for comparing: a color parameter; a symmetry parameter; and a border parameter, an automation unit coupled to the graphical user interface for enabling a time-based synchronization of the frequently asked questionnaire unit, the scoring module, and the comparison module, and a learning unit coupled to the automation unit for activating: a user training module, an article module coupled to the user training module, a blogging unit coupled to the user training module and the article module, and a report unit including an email unit for emailing health related information.
  • the camera comprises a tracking unit for tracking at least one of skin spots over time, laser treatment effectiveness, cellulite content in skin, current tan level, condition of veins and capillaries, Botox treatment effectiveness, anti-aging treatment effectiveness, anti-acne treatment effectiveness, and a pictorial history of skin to be given to the doctor.
  • the skin spots over time include at least one of blemishes, scars, rashes, lesions, and moles.
  • the web-enabled computing system for uploading the photograph captured by the camera further includes a walkthrough module for walking through features of a skin health record of a first time user of the system, a personal skin photo album for reviewing pictorial history of a regular user of the system, and a product quality menu for tracking product expiration dates.
  • the interface for uploading the photograph further includes a reminder unit for next photo for a regular user of the system; and a cosmetic status unit coupled to the reminder unit for displaying a current usage of a cosmetic for the regular user of the system.
  • the current usage comprises a usage of at least one of a moisturizer, an antiseptic, a toner, a laser, and a Botox.
  • the system and method may further include a photo review unit for date based reviewing of at least one of a condition of a predetermined body part, a current usage status of a cosmetic, and a recommended usage list of cosmetics.
  • the report unit may further include a secure transmission unit for sending a health assessment report to a medical practitioner, an affinity unit for discussing health assessment data with a friend, and a printing unit for printing health assessment data.
  • a mobile device-based health assessment system and method may include a photograph capturing device for capturing a skin image of a mobile device user, a transmission unit coupled with the photograph capturing device for uploading the captured skin image to a network location, a global positioning device coupled to the photograph capturing device for determining a location of the photograph capturing device, and a weather estimation device coupled to the photograph capturing device to determine a weather condition at a location of the mobile device user to thereby obtain a remote diagnosis report.
  • the photograph capturing device further comprises at least one of a skin photograph assessment unit, a nail photograph assessment unit, and a hair photograph assessment unit.
  • the global positioning device comprises a location tracker for answering user raised questions pertaining to geographical positioning of the user.
  • the location tracker includes a database pertaining to weather intensive cosmetics.
  • the system and method may further include a phone number tracker for enabling a mobile device user to contact health assessment and cosmetic outlets.
  • a system and method for estimation of skin type and skin features to create a unique spectral signature may include convoluting data from a first image captured in incident diffuse white light, wherein the data relate to reflected and/or re-emitted polarized or white light, convoluting data from a second image captured in incident polarized light, wherein the data relate to reflected and/or re-emitted polarized light, comparing extreme positions of at least two unique convolutions generated by convoluting data from the first image and the second image, and determining a distance between minimum and maximum intensity positions in convoluted red minus blue spectral plots from the at least two unique convolutions for generating a numerical skin type output.
  • the physiological white light comprises three spectral intervals including a width less than 100 nanometer.
  • the three spectral intervals pertain to red, green, and blue (RGB) colors.
  • the three spectral intervals provide a natural white light sensation to a human eye.
  • the step of comparing extreme positions of at least two unique convolutions comprises comparing a component (R- B)(W-P) for the reflected and/or re-emitted polarized light, and a component (R-B)W for the white light.
  • the two unique convolutions in white light and polarized light further include a White Red component (WR), a White Blue component (WB), a reflected and/or re-emitted Polarized Blue component (PB) and a reflected and/or re-emitted Polarized Red component (PR).
  • the two unique convolutions are based on a numerical value difference correlating to medical standards.
  • the system and method may further include a spectral convolution scheme wherein multiple combinations of subtraction of blue spectrum from red, in white light and polarized white light are determined, wherein the spectral interval is expressed in a wavelength scale interval of 100 nanometers to 300 nanometers.
  • a system and method for creating a unique spectral signature of skin features may include a RGB (Red Green Blue) color channel spectral plot generated from digital images including single wavelength light matter interaction thereby generating skin type characterization output, skin moisture conductivity and skin elasticity in numerical and descriptive standards.
  • the RGB (Red Green Blue) color channel spectral plots generated from digital images include multi-wavelength light matter interaction.
  • a system and method to track and store movement parameters of an imaging device moving over a subject area may include the steps of capturing an image of the subject area at a plurality of locations, identifying a direction of movement of the imaging device using an image processing technique for at least one captured frame, recognizing the direction of movement of the imaging device by comparing each frame with at least three distinct features captured to thereby triangulate a location of the imaging device, and comparing data of the captured image with a predetermined image database to store the image of the subject area and to store placement parameters of the imaging device.
  • the step of capturing the image of the subject area at a plurality of locations comprises a sub step of capturing a continuous video image of the subject area.
  • the step of capturing the image of the subject area at a plurality of locations comprises a sub step of capturing a frame by frame sequence of images of the subject area.
  • the step of identifying a direction of movement of the imaging device using an image processing technique comprises a sub-step of a frame by frame comparison of the captured image to identify movement parameters of the imaging device.
  • the step of recognizing the direction of movement of the imaging device by comparing each frame with at least three distinct features captured to triangulate a location of the imaging device comprises a sub-step of capturing a direction of movement of the imaging device by comparing three or more distinct positions across different frames.
  • an automated location tracking and data storage method and system for an imaging device may include an image capturing unit, a positioning unit coupled to the image capturing unit for positioning the imaging device on a subject area, and an image processing unit for enabling a frame by frame comparison of the captured image and for enabling the imaging device to capture three or more distinct points to triangulate a location of the imaging device to identify a direction of movement of the imaging device.
  • the image capturing unit comprises a digital camera.
  • the image capturing unit comprises at least one of a mobile device and a Personal Digital Assistant (PDA).
  • PDA Personal Digital Assistant
  • the image processing unit comprises a comparison unit for comparing positions of three or more distinct points across different frames to capture direction of movement of the imaging device.
  • the system and method may further include a subsystem for measuring lateral motion of the image capturing unit from a predetermined point to a new location on the subject area.
  • a system and method for determining a surgical excision margin may include illuminating a melanocytic lesion skin with an incident light source, detecting a characteristic of the light reflected and/or re-emitted from the melanocytic lesion, and determining a border between the melanocytic lesion and surrounding healthy tissue based on at least one characteristic of the reflected and/or re-emitted light.
  • the incident light is directed at a selected angle alpha.
  • varying alpha varies the depth of the measurement of the layers in the melanocytic lesion. Each depth has a specific angle which produces a full polarized reflection.
  • the incident light is unpolarized light.
  • the unpolarized light is at least one of white light, light of a single wavelength, and light of multiple single wavelengths.
  • the incident light is polarized light.
  • the reflected and/or re-emitted light is at least one of polarized light and unpolarized light.
  • the characteristic is at least one of light source, light intensity, wavelength of light, angle of light, electrical and magnetic properties of the light, and polarization state of the light.
  • An aspect of the polarization is at least one of an orientation, an amplitude, a phase, an angle, a shape, a degree, and an amount.
  • determining is done using an algorithm.
  • the algorithm involves at least one of artificial neural networks, fuzzy logic, fractal and multi-fractal analysis, non-linear regression, a genetic algorithm, white light analysis and RGB color analysis.
  • the system and method may further include filtering the reflected and/or re-emitted light to obtain light of a wavelength defined by the filter output. Algorithmic analysis is performed on the filtered image.
  • determining involves creating an image of the difference between reflected diffusion light and reflected polarized light.
  • determining involves comparing the aspect of the polarization of the reflected and/or re-emitted light to a calibration signal.
  • determining further comprises considering at least one of user input and a visual analysis.
  • a handheld device for capture or acquisition of an image of an individual tooth, the gums, or the entire set of teeth.
  • the device can be handheld and a person can perform sweeping motion to take an image of the entire dental set.
  • the device facilitates creation or generation of a 3D model of the teeth for analysis of pre-existing conditions thereof, facilitates measurement of the health of a tooth and determination of the health of the tooth, such as in a cautionary status or needs intervention and maintenance of photo record of the teeth.
  • the methods and systems for overall management of dental or oral health performs one or more functions.
  • the methods and systems for overall management of dental or oral health exhibition of degree of mineralization of enamel and ratio of minerals to water and other organic material thereof, color of enamel, comparison of enamel over time, validation of a person's hygienic routine by determining progress of enamel cleaning, thickness of enamel, health of cementoenamel junction (or CEJ), measurement of strength on a relative scale or in comparison with peers, on custom scales or on Mohs hardness scale, for example, presence of proteins called amelogenins and enamelins, determination of type of Dentin, such as primary, secondary and tertiary, porosity, verification of the health and status of a teeth enamel and other dermal structures thereof, determination of depth of enamel towards application, determination of predisposition of dental cavities and other dental problems, identification and presence of rod sheath, Striae of Ret
  • a device and method for determining the opto-magnetic fingerprints of different food materials in different states and comparing the fingerprints of different food materials in different states with the fingerprints of known materials in different states is disclosed.
  • a device may have an illumination source, a sensor for measuring the opto-magnetic properties of the food materials, and a module for characterizing the material based on a comparison of the fingerprints of different food materials in different states with the fingerprints of known materials in different states.
  • Fig. 1 depicts a skin care system for skin health analysis and monitoring, and skin care assessment and recommendation.
  • Fig. 2 depicts a mechanism for light polarization by a skin structure.
  • Fig. 3 depicts a process for skin care examination.
  • Fig. 4A & B depict a front and back view of a dermal imaging device.
  • Fig. 5 depicts a skin health monitoring page of a skin care system.
  • Fig. 6 depicts an interactive modeling tool of a skin care system.
  • Fig. 7 depicts a recommendations page of a skin care system.
  • Fig. 8 depicts a user interface of a skin care system.
  • Fig. 9 depicts a welcome page of a skin care system.
  • Fig. 10 depicts a questionnaire page of a skin care system.
  • Fig. 1 1 depicts a skin image capture page of a skin care system.
  • Fig. 12 depicts a results page with bar graphs of a skin care system.
  • Fig. 13 depicts a results page with line graphs of a skin care system.
  • Fig. 14 depicts a summary screen of a skin care system.
  • Fig. 15 depicts an elasticity summary screen of a skin care system.
  • Fig. 16 depicts a summary screen of a skin care system.
  • Fig. 17 depicts an elasticity summary screen of a skin care system.
  • Fig. 18 depicts a map of a user interface for a skin care system.
  • Fig. 19 depicts a review page of a skin care system.
  • Fig. 20 depicts a review page of a skin care system.
  • Fig. 21 depicts a My Experience page of a skin care system.
  • Fig. 22 depicts a What Works page of a skin care system.
  • Fig. 23 depicts an Info For Me page of a skin care system.
  • Fig. 24 depicts an example of a skin care shelf portion of a user interface of a skin care system.
  • Fig. 25 depicts an example of a skin care shelf portion of a user interface of a skin care system.
  • Fig. 26 depicts a user interface of a skin care system.
  • Fig. 27 depicts a registration page of a skin care system.
  • Fig. 28 depicts a recommendation page of a skin care system.
  • Fig. 29 depicts a mobile content map for a mobile user interface of a skin care system.
  • Fig. 30 depicts a How Good Is This Product message flow.
  • Fig. 31 depicts a What Should I Look For? message flow
  • Fig. 32 depicts a Suncheck message flow.
  • Fig. 33 depicts an Alert message flow.
  • Fig. 34 depicts an Options message flow.
  • Fig. 35 depicts an algorithm and method for analyzing materials.
  • Fig. 36 depicts the reflection and capture of white light and reflected polarized light from a specimen based on varying angles.
  • Figs. 37A&B depict color coordinate systems that can be used in digital image processing.
  • Fig. 38 depicts a histogram of color density.
  • Fig. 39 depicts a normalized color channel histogram correlated to wavelength scale.
  • Fig. 40 depicts overlaid, normalized color channel histograms.
  • Fig. 41 depicts a convolution of individual color channel histograms.
  • Fig. 42 depicts the combination of the two convolutions of the two color channel histograms.
  • Fig. 43 depicts a mathematical modeling of a portion of Maxwell's color triangle.
  • Figs. 44A & B depict the resulting spectral signatures for light and dark skin.
  • Figs. 45A - C depict the resulting spectral signatures for pure and alloy metals.
  • Figs. 46A & B depict the resulting spectral signatures for different types of water.
  • Fig. 47 depicts a block diagram of a skin care device embodiment.
  • Fig. 48 depicts a wand-shaped skin care device embodiment.
  • Fig. 49 depicts a vertical display panel including skin care device.
  • Fig. 50 depicts an embodiment of a wearable skin care device.
  • Fig. 51 depicts positive and negative intensities on a waveform as a function of emission and absorption of specific wavelengths within skin tissue.
  • Fig. 52 depicts the comparison between spectral signatures of healthy skin and malignant skin around a reference wavelength.
  • Fig. 53 depicts malignant pigmented skin in white and physiologically polarized white light.
  • Fig. 54 depicts the comparison of convolutions between healthy, benign and malignant skin lesions.
  • Fig. 55 depicts a system for tracking and targeting an image.
  • Fig. 56 depicts a system for determining an excision margin.
  • Fig. 57 depicts a system for determining an excision margin.
  • Fig. 58 is a flowchart illustrating a process for RGB color analysis.
  • Fig. 59 is a diagram depicting a pixel view of an acquired digital image of a sample of person's skin.
  • Fig. 60 is a diagram depicting a pixel view of the acquired digital image of a sample of person's skin after quantization.
  • Fig. 61 is a diagram depicting a Histogram / Distribution of standard R, G and B colors on one of the taken photographs of a patient whose skin phototype is classified as type III by Fitzpatrick, and their Gaussian normal approximation / hull.
  • Fig. 62 is a diagram depicting a Histogram / Distribution of standard R, G and B colors on one of the patient's photographs whose skin phototype is classified as type VI by Fitzpatrick, and their Gaussian normal approximation / hull.
  • Fig. 63 is a flowchart illustrating an algorithm for determining the skin phototype according to the estimated values of mathematical expectation for R and B colors in a standard RGB color system.
  • Fig. 64 depicts an embodiment of a friend toolbar.
  • Fig. 65 depicts the auto-scroll feature of the friend toolbar.
  • Fig. 66 depicts the drag-and-drop share functionality of the friend toolbar.
  • Fig. 67 depicts the drag-and-drop share functionality of the friend toolbar.
  • Fig. 68 depicts sharing skin data as a data object with friends.
  • Fig. 69 depicts posting skin care data as a data object on a blog or forum where users may discuss the data.
  • Fig. 70 depicts sharing skin data as a data object where the data object becomes part of the content that a user may wish to discuss.
  • FIG. 71 is a schematic view of a system for automated diagnosis of skin disorders by image processing detection of skin lesions or dermascopic structures, designed and implemented in accordance with at least some embodiments of the invention.
  • FIG. 72 is an exploded diagrammatic representation of the host computing subsystem, of Fig. 1 , comprising the skin disorder management module designed and implemented in accordance with at least some embodiments of the invention.
  • FIG. 73 is a block diagrammatic view of a system facilitating implementation of an Opto-Magnetic process based on light-matter interaction using digital imaging for detection of EPV and CMV viruses in blood plasma samples, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 74 is an exploded diagrammatic representation of the host computing subsystem, of the Fig. 1 , comprising the Opto-Magnetic Fingerprint (or OMF) Generator module designed and implemented in accordance with at least some embodiments of the invention;
  • FIG. 75 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 1 and 2 thereby facilitating estimation of blood plasma type and properties (or characteristics) thereof and creation of a unique spectral signature;
  • FIGS. 76A and 76B depict a dual pair of typical digital images of samples, tested positive and negative for EBV and CMV, captured with diffuse white light (W) and reflected polarized light (P), in that order;
  • FIGS. 77A and 77B depict a first pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a first set of two patients subjected to a first test case for confirmation of EBV, namely "Case I: EBV-lgM", designed and implemented in accordance with certain embodiments of the invention;
  • FIGS. 78A and 78B depict a second pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a second set of two different patients subjected to a second test case for confirmation of EBV, namely "Case II: EBV-lgM", designed and implemented in accordance with certain embodiments of the invention; [00186] FIGS.
  • 79A and 79B depict a third pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a third set of two different patients subjected to a third test case for confirmation of EBV, namely "Case III: EBV-lgG", designed and implemented in accordance with certain embodiments of the invention;
  • FIGS. 80A and 80B depict a fourth pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a fourth set of two different patients subjected to a fourth test case for confirmation of EBV, namely "Case IV: EBV-lgG", designed and implemented in accordance with certain embodiments of the invention;
  • FIG. 81 is a block diagrammatic view of a system facilitating implementation of an Opto-Magnetic process based on light-matter interaction using digital imaging for Papanicolau Test Analysis of samples, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 82 is an exploded diagrammatic representation of the host computing subsystem, of Fig. 81 , comprising the Opto-Magnetic Fingerprint (or OMF) Generator module designed and implemented in accordance with at least some embodiments;
  • FIG. 83 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 81 and 82 thereby facilitating estimation of Pap test sample type and properties (or characteristics) thereof and creation of a unique spectral signature;
  • FIGS. 84A-B, 85A-B and 86A-B depict a triple pair of typical digital images of samples (or Pap smear slides), categorized as Group I (or normal tissue state), captured with diffuse white light (W) and reflected polarized light (P), in that order;
  • FIG. 84C depicts a plot of typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of FIGS. 84A-B of the given, selected first sample (or Pap smear slide) categorized as Group I (or normal tissue state), in accordance with certain embodiments of the invention;
  • FIG. 85C depicts a plot of typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of FIGS. 85A-B of the given, selected second sample (or Pap smear slide) categorized as Group I (or normal tissue state), in accordance with certain embodiments of the invention;
  • FIG. 86C depicts a plot of typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of FIGS. 86A-B of the given, selected third sample (or Pap smear slide) categorized as Group I (or normal tissue state), in accordance with certain embodiments of the invention;
  • FIG. 87 depicts a plot of typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of a given, selected sample (or Pap smear slide) categorized as Group II (or non-typical inflammation), in accordance with certain embodiments of the invention
  • FIG. 88 depicts a plot of typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of a given, selected sample (or Pap smear slide) categorized as Group III (dysplasia), in accordance with certain embodiments of the invention
  • FIG. 89 depicts a plot of typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of a given, selected sample (or Pap smear slide) categorized as Group IV (carcinoma in situ), in accordance with certain embodiments of the invention
  • FIG. 90 depicts a plot of typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of a given, selected sample (or Pap smear slide) categorized as Group V (suspicion to carcinoma), in accordance with certain embodiments of the invention
  • FIG. 91 depicts a system for generating enhanced heterogeneous signals for use in non-invasive processing of materials utilizing an Opto-Magnetic Antenna (or OMA), designed and implemented in accordance with certain embodiments of the invention
  • FIG. 92 is block diagrammatic view of at least one workable configuration for use in tandem with the system of FIG. 91 ;
  • FIG. 93 depicts a flow diagram delineating at least one process implemented by the system configuration of FIG. 92 thereby facilitating multi sensor high frequency imaging;
  • FIG. 94 is a schematic view of a wearable computing system for monitoring of one or more physiological parameters designed and implemented in accordance with at least some embodiments of the invention.
  • FIG. 95 is an exploded diagrammatic representation of the host computing subsystem, of Fig. 94, comprising the skin hydration management module designed and implemented in accordance with at least some embodiments of the invention;
  • FIG. 96 is a perspective view of the WHM of FIG. 94 designed and implemented as a handheld monitor for measurement of hydration status, in accordance with some other embodiments of the invention.
  • FIG. 97 is a diagram depicting an image of area to be excised
  • FIG. 98 is a diagram depicting the process employed for automatically determining the area to be excised
  • FIG. 99 is a diagram depicting a system for distinguishing between a healthy skin biological tissue and an unhealthy biological skin tissue for enabling an excision proximate to the healthy biological tissue;
  • FIG. 100 is a schematic diagram depicting a system for determining a predisposition of sebaceous pores and skin structures
  • FIG. 101 is a flowchart illustrating a process for generating a skin phototype, in accordance with an aspect of the present technique.
  • FIG. 102 is a diagram depicting reflectance of spectral rays (diffusely reflected spectral rays) in all directions from the surface of the skin.
  • FIG. 103 depicts Opto-magnetic diagrams for 18.2 ⁇ water at -4.4 °C
  • FIG. 105 is a block diagrammatic view of a system facilitating overall management of dental or oral health through implementation of an Opto-Magnetic process based on light-matter interaction using digital imaging for diagnosis of teeth, designed and implemented in accordance with certain embodiments of the invention;
  • FIG. 106 is an exploded diagrammatic representation of the host computing subsystem, of the Fig. 105, comprising an Opto-Magnetic Fingerprint (or OMF) Generator sub-module designed and implemented in accordance with at least some embodiments;
  • OMF Opto-Magnetic Fingerprint
  • FIG. 107 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 105 and 106 thereby facilitating determination of teeth type and properties (or characteristics) thereof and creation of a unique spectral signature;
  • FIG. 108 depicts a first plot of a typical spectral data (or OMF diagram) for enamel obtained on implementation of the OMF method on digital images of the teeth, in accordance with certain embodiments of the invention
  • FIG. 109 depicts a second plot of a typical spectral data (or OMF diagram) for dentin obtained on implementation of the OMF method on digital images of the teeth, in accordance with certain embodiments of the invention.
  • FIG. 110 depicts a third plot of a typical spectral data (or OMF diagram) of cement obtained on implementation of the OMF method on digital images of the teeth, in accordance with certain embodiments of the invention
  • FIG. 11 1 A is a block diagrammatic view of a system facilitating overall management of dental or oral health through implementation of an Opto-Magnetic process based on light-matter interaction using digital imaging for diagnosis of teeth, designed and implemented in accordance with certain embodiments of the invention;
  • FIG. 1 1 B depicts an intraoral camera specification.
  • FIG. 112 is an exploded diagrammatic representation of the host computing subsystem, of the Fig. 11 1A, comprising an Opto-Magnetic Fingerprint (or OMF) Generator sub-module designed and implemented in accordance with at least some embodiments;
  • OMF Opto-Magnetic Fingerprint
  • FIG. 113 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 1 1 1A and 112 thereby facilitating determination of teeth type and properties (or characteristics) thereof and creation of a unique spectral signature;
  • FIG. 114 depicts a first plot of a typical spectral data (or OMF diagram) for enamel obtained on implementation of the OMF method on digital images of the teeth, in accordance with certain embodiments of the invention
  • FIG. 1 15 depicts a second plot of a typical spectral data (or OMF diagram) for dentin obtained on implementation of the OMF method on digital images of the teeth, in accordance with certain embodiments of the invention;
  • FIG. 116 depicts a third plot of a typical spectral data (or OMF diagram) of cement obtained on implementation of the OMF method on digital images of the teeth, in accordance with certain embodiments of the invention;
  • FIG. 1 17 depicts a pair of snapshots of a pair of canine teeth prior and subsequent to cross- sectional cutting in juxtaposition with a third snapshot depicting main dental tissues thereof for clarification purposes;
  • FIG. 1 18 depicts the results of the implementation of the OMF method on 44 cross-sections on multiple locations and the high sensitivity of the OMF method in terms of wavelength and reflected light intensities;
  • FIG. 119A depicts images for the comparative analysis of the teeth with healthy enamel obtained using AFM / MFM and OMF methods, in accordance with the principles of the invention
  • FIG. 119B depicts images for the comparative analysis of the teeth with enamel affected with caries obtained using AFM / MFM and OMF methods, in accordance with the principles of the invention
  • FIG. 1 19C depicts images for the comparative analysis of the teeth with healthy dentin obtained using AFM / MFM and OMF methods, in accordance with the principles of the invention
  • FIG. 1 19D depicts images for the comparative analysis of the teeth with dentin affected with caries obtained using AFM / MFM and OMF methods, in accordance with the principles of the invention
  • FIG. 119E depicts images for the comparative analysis of the teeth with healthy cement obtained using AFM / MFM and OMF methods, in accordance with the principles of the invention
  • FIG. 119F depicts images for the comparative analysis of the teeth with cement affected with caries obtained using AFM / MFM and OMF methods, in accordance with the principles of the invention
  • FIG. 120 is a block diagrammatic view of a system facilitating implementation of an Opto- Magnetic process based on light-water interaction using digital imaging for analysis of water samples, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 121 is an exploded diagrammatic representation of the host computing subsystem, of the FIG. 120, comprising an Opto-Magnetic Fingerprint (or OMF) Generator sub-module designed and implemented in accordance with at least some embodiments;
  • OMF Opto-Magnetic Fingerprint
  • FIG. 122 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 120 and 121 thereby facilitating estimation of water sample type and properties (or characteristics) thereof and creation of a unique spectral signature;
  • FIGS. 123A-B depict a first pair of plots for typical spectral data (or OMF diagrams) obtained by the device facilitating implementation of the OMF method on digital images of the given, selected first pair of samples at a given, selected first temperature for characterization of the same in magnetic and electric domains, in accordance with certain embodiments of the invention
  • FIGS. 124A-B depict a second pair of plots for typical spectral data (or OMF diagrams) obtained by the device facilitating implementation of the OMF method on digital images of the given, selected second pair samples at a given, selected second temperature for characterization of the same in magnetic and electric domains, in accordance with certain embodiments of the invention
  • FIGS. 125A-B depict plots possessing specifications and associated analytical information including Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values in accordance with certain embodiments of the invention;
  • FIGS. 126A-B depict a fourth pair of plots for typical spectral data (or OMF diagrams) obtained by the device facilitating implementation of the OMF method on digital images of the given, selected fourth pair of samples at a given, selected fourth temperature for characterization of the same in magnetic and electric domains, in accordance with certain embodiments of the invention
  • FIGS. 127A-B depict a fifth pair of plots for typical spectral data (or OMF diagrams) obtained by the device facilitating implementation of the OMF method on digital images of the given, selected fifth pair of samples at the given, selected second temperature and under the influence a given, selected magnetic flux density for a given, selected time duration for characterization of the samples in magnetic and electric domains, in accordance with certain embodiments of the invention;
  • FIGS. 128A-B depict a sixth pair of plots for typical spectral data (or OMF diagrams) obtained by the device facilitating implementation of the OMF method on digital images of the given, selected sixth pair of samples at the given, selected second temperature and under the influence a changeable (or exchangeable) magnetic flux density (or magnetic field intensity) for characterization of the samples in magnetic and electric domains, in accordance with certain embodiments of the invention;
  • FIG. 129A is a block diagrammatic view of a system facilitating implementation of an Opto- Magnetic process based on light-matter interaction using digital imaging for analysis of skin samples, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 129B is an exploded diagrammatic representation of the IS 12900 designed and implemented in accordance with at least some embodiments;
  • FIG. 130A is an exploded diagrammatic representation of the host computing subsystem, of the FIG. 129A, comprising an Opto-Magnetic Fingerprint (or OMF) Generator sub-module designed and implemented in accordance with at least some embodiments;
  • OMF Opto-Magnetic Fingerprint
  • FIG. 130B is a top view of the IS 12900 assembly illustrated in conjunction with FIG. 129A;
  • FIG. 130C depicts a cross-sectional view of the IS 12900 along a section line D-D thereof;
  • FIG. 130D is an exploded view of Optoelectronics sub-assembly, constituting the IS 12900 assembly, designed and implemented in accordance with certain embodiments of the invention.
  • FIG. 130E is an exploded view of handle and cradle sub-assembly, constituting the constituting the IS 12900 assembly, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 130F is an exploded view of the Optoelectronics sub-assembly incorporated in the handle and cradle sub-assembly, designed and implemented in accordance with certain embodiments of the invention;
  • FIG. 131 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 129A-B and 130A-F thereby facilitating estimation of skin sample type and properties (or characteristics) thereof and creation of a unique spectral signature;
  • FIG. 132A is a block diagrammatic view of a system facilitating implementation of an Opto- Magnetic process based on light-matter interaction using digital imaging for analysis of skin samples, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 132B is an exploded diagrammatic representation of the IS 13200 designed and implemented in accordance with at least some embodiments;
  • FIG. 133A is an exploded diagrammatic representation of the host computing subsystem, of the FIGS. 132A-B, comprising an Opto-Magnetic Fingerprint (or OMF) Generator sub-module designed and implemented in accordance with at least some embodiments;
  • OMF Opto-Magnetic Fingerprint
  • FIG. 133B depicts a sample embodiment of an optoelectronics apparatus designed and implemented in accordance with at least some embodiments
  • FIG. 134 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 132A-B and 133A-B thereby facilitating estimation of skin sample type and properties (or characteristics) thereof and creation of a unique spectral signature;
  • FIG. 135 is a block diagrammatic view of an improved system facilitating implementation of an Opto-Magnetic process based on light-matter interaction using lens-free digital imaging for analysis of skin samples, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 136 is a block diagrammatic view of a system facilitating implementation of an Opto- Magnetic process based on light-matter interaction using digital imaging for characterization of samples of skin, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 137 is an exploded diagrammatic representation of the host computing subsystem, of the FIG. 136, comprising an Opto-Magnetic Fingerprint (or OMF) Generator sub-module designed and implemented in accordance with at least some embodiments;
  • OMF Opto-Magnetic Fingerprint
  • FIG. 138 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 136 and 137 thereby facilitating estimation of skin test sample type and properties (or characteristics) thereof and creation of a unique spectral signature;
  • FIG. 139 is a cross-sectional anatomical view of the epidermis with four main layers, basement membrane and other structures including, but not limited to, melanocyte, Langerhans cell, in accordance with the prior art and adapted therefrom;
  • FIGS. 140A-C depicts three distinct snapshots of epidermis of human skin, and layers thereof, juxtaposed to each other, in accordance with the prior art and adapted therefrom;
  • FIG. 141A depicts a first plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of skin layers, confined to the inner arm region, captured from a given, selected first sample procured from a given, selected first male subject or volunteer aged 1 1 years, in accordance with certain embodiments of the invention;
  • FIG. 141 B depicts a second plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of the Layer "1 " of skin, disclosed in conjunction with FIG. 139, and confined to the inner arm region, in which the digital images captured from a given, selected second sample procured from the given, selected first male subject or volunteer aged 1 1 years, in accordance with certain embodiments of the invention;
  • FIG. 141 C depicts a third plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected third sample procured from a third selected layer confined to the inner arm region, of skin of the given, selected first male subject or volunteer aged 1 1 years, in accordance with certain embodiments of the invention;
  • FIG. 141 D depicts a fourth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected fourth sample procured from a fourth selected layer confined to the inner arm region of skin of the given, selected first male subject or volunteer aged 1 1 years, in accordance with certain embodiments of the invention;
  • FIG. 142A depicts a fifth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected fifth sample procured from the given, selected first layer confined to the inner arm region of skin of the given, selected second male subject or volunteer aged 63 years, in accordance with certain embodiments of the invention;
  • FIG. 142B depicts a sixth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected sixth sample procured from the given, selected second layer confined to the inner arm region of skin of the given, selected second male subject or volunteer aged 63 years, in accordance with certain embodiments of the invention;
  • FIG. 142C depicts a seventh plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected seventh sample procured from the given, selected third layer confined to the inner arm region of skin of the given, selected second male subject or volunteer aged 63 years, in accordance with certain embodiments of the invention;
  • FIG. 142D depicts an eighth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected eighth sample procured from the given, selected fourth layer confined to the inner arm region of skin of the given, selected second male subject or volunteer aged 63 years, in accordance with certain embodiments of the invention;
  • FIG. 143A depicts a ninth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected ninth sample procured from the given, selected first layer confined to the inner arm region of skin of the given, selected third male subject or volunteer aged 50 years, in accordance with certain embodiments of the invention;
  • FIG. 143B depicts a tenth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected tenth sample procured from the given, selected second layer confined to the inner arm region of skin of the given, selected third male subject or volunteer aged 50 years, in accordance with certain embodiments of the invention;
  • FIG. 143C depicts an eleventh plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected eleventh sample procured from the given, selected third layer confined to the inner arm region of skin of the given, selected third male subject or volunteer aged 50 years, in accordance with certain embodiments of the invention;
  • FIG. 143D depicts a twelfth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected twelfth sample procured from the given, selected fourth layer confined to the inner arm region of skin of the given, selected third male subject or volunteer aged 50 years, in accordance with certain embodiments of the invention;
  • FIG. 144A depicts a thirteenth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected thirteenth sample procured from the given, selected first layer confined to the inner arm region of skin of the given, selected fourth male subject or volunteer aged 43 years, in accordance with certain embodiments of the invention;
  • FIG. 144B depicts a fourteenth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected fourteenth sample procured from the given, selected second layer confined to the inner arm region of skin of the given, selected fourth male subject or volunteer aged 43 years, in accordance with certain embodiments of the invention;
  • FIG. 144C depicts a fifteenth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected fifteenth sample procured from the given, selected third layer confined to the inner arm region of skin of the given, selected fourth male subject or volunteer aged 43 years, in accordance with certain embodiments of the invention;
  • FIG. 144D depicts a sixteenth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected sixteenth sample procured from the given, selected fourth layer confined to the inner arm region of skin of the given, selected fourth male subject or volunteer aged 43 years, in accordance with certain embodiments of the invention;
  • FIG. 145 depicts a three-dimensional (or 3-D) Atomic Force Microscopy (or AFM) image of skin on removal of the Layer "3", in accordance with certain embodiments of the invention
  • FIG. 146A depicts a seventeenth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected seventeenth sample procured from the given, selected third layer confined to the inner arm region of skin of the given, selected first male subject or volunteer aged 1 1 years, in accordance with certain embodiments of the invention; [00281] FIG.
  • 146B depicts an eighteenth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected eighteenth sample procured from the given, selected third layer confined to the inner arm region of skin of the given, selected second male subject or volunteer aged 63 years, in accordance with certain embodiments of the invention;
  • FIG. 146C depicts an nineteenth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected nineteenth sample procured from the given, selected third layer confined to the inner arm region of skin of the given, selected third male subject or volunteer aged 50 years, in accordance with certain embodiments of the invention;
  • FIG. 146D depicts a twentieth plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images captured from of a given, selected twentieth sample procured from the given, selected third layer confined to the inner arm region of skin of the given, selected fourth male subject or volunteer aged 43 years, in accordance with certain embodiments of the invention;
  • FIG. 147 depicts a graphical representation of bioimpedance versus skin layers obtained on implementation of bioimpedance measurements on one or more samples procured from corresponding one or more layers confined to the inner arm region of skin of the given, selected first and second male subjects aged 1 1 and 63 years, in accordance with certain embodiments of the invention
  • FIG. 148 is a block diagrammatic view of a system facilitating implementation of a process using a pair of electrodes for measurement of skin impedance, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 149 depicts an equivalent circuit Cole mathematical model for calculation of the electrical impedance of the skin, partly in accordance with the prior art and adapted therefrom;
  • FIG. 150 depicts a plot for bioimpendance of human skin for a voltage amplitude of 0.1V and diameter of electrodes is 2 cm;
  • FIG. 151 depicts a plot for a robust fit one-Cole model, "bisquare" -method, designed and implemented in accordance with certain embodiments of the invention
  • FIG. 152 depicts a plot for Levenberg-Marquardt nonlinear least squares fit one-Cole model, in accordance with certain embodiments of the invention.
  • FIG. 154 is a block diagrammatic view of a system facilitating organ (or bio) printing deployed in conjunction with the system configuration of FIGS. 129A-B and 130A-F, designed and implemented in accordance with certain embodiments of the invention.
  • FIG. 155 shows an exemplary device that can be used for checking food quality.
  • FIG. 156 shows an exemplary flowchart of a method that can be used for checking food quality.
  • FIG. 157 shows an exemplary spectral chart for lamb meat in four different states.
  • FIG. 158 shows an exemplary scores plot for frozen lamb meat.
  • FIG. 159 shows an exemplary loadings plot for frozen lamb meat.
  • FIG. 160 shows an exemplary scores plot for lamb at room temperature.
  • FIG. 161 shows an exemplary loadings plot for lamb at room temperature.
  • FIG. 162 shows an exemplary scores plot for frozen beef.
  • FIG. 163 shows an exemplary loadings plot for frozen beef.
  • FIG. 164 shows an exemplary scores plot for beef at room temperature.
  • FIG. 165 shows an exemplary loadings plot for beef at room temperature.
  • FIG. 166 shows an exemplary scores plot for frozen swine meat.
  • FIG. 167 shows an exemplary loadings plot for frozen swine meat.
  • FIG. 168 shows an exemplary scores plot for swine meat at room temperature.
  • FIG. 169 shows an exemplary loadings plot for swine meat at room temperature
  • FIG. 170 shows an exemplary scores plot for frozen veal meat.
  • FIG. 171 shows an exemplary loadings plot for frozen veal meat.
  • FIG. 172 shows an exemplary scores plot for veal meat at room temperature.
  • FIG. 173 shows an exemplary loadings plot for veal meat at room temperature.
  • Real-time analysis of digitally captured skin-related and other information may facilitate real-time skin condition assessment, real-time skin regimen recommendation, and real-time evaluation of the effectiveness of a selected skin regimen.
  • Real-time analysis of digitally captured data may be performed by using a skin care device embodying the principles of the invention disclosed herein.
  • a skin care device embodying the principles of the invention may include, for example, an electromagnetic radiation source capable of directing incident electromagnetic radiation, a radiation detector for measuring various parameters of the re-emitted radiation, and a skin condition analysis module capable of generating a skin condition assessment in real-time.
  • the skin condition assessment may be cosmetic and/or medical in nature.
  • the skin condition assessment may include any one of an acne condition assessment, a pore condition assessment, a wrinkle condition assessment, a skin elasticity assessment, a skin oiliness assessment, a skin moisture assessment, a skin luminosity assessment, a skin sebum assessment, a skin redness assessment, a skin inflammation assessment, a skin texture assessment, a skin color assessment or any combination of the listed assessments.
  • the pore condition assessment can help in determining whether the pores are clean, open and of optimal health.
  • Skin-condition data may be acquired, for example, by directing incident electromagnetic radiation to a location, such as a pin-point location, on the skin of a person and detecting the re-emitted radiation from the location by using a radiation detector.
  • the effectiveness of generating high-quality, real-time skin condition assessments may be enhanced in some embodiments by using a skin condition analysis module that bases its analysis at least partly on diffused reflectance spectroscopy.
  • the quality of real-time skin condition assessments may be further enhanced in other embodiments by using white light as the incident radiation and by detecting the red-green-blue components of the re-emitted light.
  • digital image refers to a representation of a two-dimensional image using ones and zeros (or binary digits or bits).
  • the digital image may be of vector or raster type depending on whether or not the image resolution is fixed. However, without qualifications the term “digital image” usually refers to raster images.
  • image processing refers to any form of signal processing for which the input is an image, such as photographs or frames of video.
  • the output of image processing can be either an image or a set of characteristics or parameters related to the image.
  • Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal- processing techniques to it.
  • Image processing usually refers to digital image processing, but optical and analog image processing are also possible.
  • the acquisition of images, i.e. producing the input image in the first place, is referred to as imaging.
  • digital image processing refers to the use of computer algorithms to perform image processing on digital images.
  • digital image processing has many advantages over analog image processing. For example, digital image processing allows a much wider range of algorithms to be applied to the input data and can avoid problems, such as the build-up of noise and signal distortion during processing.
  • digital imaging or digital image acquisition refers to creation of digital images, typically from a physical object.
  • the term is often assumed to imply or include the processing, compression, storage, printing and display of such images.
  • Medical imaging refers to the techniques and processes used to create images of the human body (or parts thereof) for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and physiology).
  • Medical imaging As a discipline and in its widest sense, it is part of biological imaging and incorporates radiology (in the wider sense), radiological sciences, endoscopy, (medical) thermography, medical photography and microscopy (e.g. for human pathological investigations).
  • Opto-magnetic fingerprinting is a simple technology that measures the interaction of light with materials to create unique "signatures.” "Signatures" can correspond to food state, material characteristics, and properties.
  • An opto-magnetic method has been developed for enhanced qualitative and quantitative parameters for detection and characterization of various biological materials. Such an opto-magnetic method based on measuring opto-magnetic properties of light-matter interaction is particularly useful for characterization and analysis of food items.
  • Such an opto-magnetic method has many advantages, including enhanced and easy interpretability, enhanced and easy detectability, enhanced sensitivity, enhanced specificity, enhanced efficiency, greater accuracy, and easy operability.
  • Such an opto-magnetic method is also rapid, economical, precise, timely, and minute variation sensitive for characterization and analysis of food samples based on opto-magnetic properties of light reflected from food materials.
  • an image of a material illuminated with incident non-angled white light and angled white light may be captured for generating a normalized red and blue color channel histogram for each image, correlating the normalized red and blue color channel histograms to a wavelength scale to obtain red and blue color channel spectral plots, and convoluting the spectral plots by subtracting the spectral plot for angled light from the spectral plot for non-angled light for each color channel to generate red and blue normalized, composite color channel spectral plots, and subtracting the normalized, composite blue channel spectral plot from the normalized, composite red channel spectral plot to generate a spectral signature for the material.
  • the illumination source may be positioned to direct light at a selected angle alpha. Varying alpha varies the depth of the measurement in the material.
  • the unit scale on the spectral signature may be a difference of wavelength.
  • the material being investigated may be inorganic and/or organic matter.
  • the spectral signature may be analyzed for at least one of the number of peaks and troughs, amplitude and shape of peaks and intermediate structures and patterns. Elements of the spectral signature may be tagged and tracked over time in order to track changes in the characteristics of the material.
  • the spectral signature may be analyzed for food materials.
  • the wavelength position of ideal blue in Maxwell's color triangle is aligned with the wavelength position of ideal red in Maxwell's color triangle when convoluting the composite spectral plots to obtain the spectral signature.
  • a system for skin health analysis, monitoring, and recommendation may comprise host hardware 108, such as an imaging device 108, for capturing biophysical skin properties such as in a skin health test 160, performing pre-diagnosis 162, and performing remote monitoring 164 using a light source 127; a user interface 102 interfacing with the host hardware 108, an online platform 120, or a mobile platform 124 for capturing demographic information, additional anecdotal information on skin health, current skin care regimen 1 18, rankings and ratings 138 of current skin care products and regimen, populating a skin care shelf 114, and accessing a skin cycle monitor 140, health and/or wellness information 142, games 148, a gift guide 144, a wish list 1 19, a Daily Report 134, simulation tools 132, a type determination engine 130, a shopping cart 1 13, and the like; a host system 104 for processing and analyzing captured information such as by employing an algorithm 150, obtaining an expert consultation 128, data integration 152, and analysis
  • An imaging device 108 may be used to capture images of skin structures to obtain biophysical skin properties such as in a skin health test 160, a pre-diagnosis 162, remote monitoring 164, and the like.
  • the imaging device 108 may also be adapted to capture images of non-dermal structures, such as hair, nails, teeth, eyes, internal organs and structures, and the like.
  • the imaging device 108 may use an internal or external light source 127 to provide a specific sequence of irradiation using unpolarized light, such as diffusion light, white light, monochromatic light, light of multiple single wavelengths, and the like, then polarized light in order to obtain data on skin structures.
  • unpolarized light such as diffusion light, white light, monochromatic light, light of multiple single wavelengths, and the like
  • the incident light may be polarized or unpolarized and the reflected or re-emitted light may be polarized or unpolarized.
  • the polarized light may result from the reflection on the skin and is not polarized from the light source. The capture and storage of the reflections enables the imaging and analysis of skin lesions, as well as all types of skin diseases, skin problems, and cosmetic concerns and indications.
  • Analysis of polarized reflections may enable obtaining thermal, electrical, and magnetic properties of the imaged skin area.
  • the images may be transmitted to an analysis facility 154, analyst, practitioner and the like, which may also include assessment with patient questionnaires, to determine a final analysis of skin health.
  • the device 108 may also employ specific targeted wavelengths, such as in the red, green, and blue areas, to identify key features, based on spectroscopic and quantitative analysis of skin lesions.
  • the device 108 may be used with diffused reflectance techniques, as well as with color imaging analysis based on indirect results from spectroscopic techniques (DR, SF, etc).
  • the device 108 may be adapted to emit polarized light.
  • the device 108 may be adapted to emit more than one type of light and may be able to switch among or combine various light sources 127.
  • the skin health analysis may be compared with a previous user skin health analysis, other users' skin health analysis, other users' experience data, and ingredient, product, and regimen characteristics to provide a recommendation for and track the effectiveness of a product or regimen 108.
  • the imaging device 108 may comprise an illumination source 127 to direct unpolarized light, diffusion light, white light, monochromatic light, light of multiple single wavelengths, polarized light, and the like, upon the skin at an angle alpha, a sensor for detecting reflected or re-emitted light from a skin structure, and an image storage device for storing and transmitting the captured images.
  • an illumination source 127 to direct unpolarized light, diffusion light, white light, monochromatic light, light of multiple single wavelengths, polarized light, and the like, upon the skin at an angle alpha
  • a sensor for detecting reflected or re-emitted light from a skin structure
  • an image storage device for storing and transmitting the captured images.
  • a skin structure may be at least one of a cell, a molecule, a group of cells, a group of molecules, an epidermis and sublayers, a basement membrane, a dermis, a subcutis, a gland, a stratum, a follicle, a pore, a vascular component, and the like resident within the skin.
  • the light source may be white light for generating reflected or re-emitted light and diffuse emission, such as polarized light, to measure the electrical and magnetic components of the skin.
  • White light may be emitted as a combination of wavelengths of light across the spectrum of visible light.
  • Incident unpolarized light may be directed at its target at a defined angle 'alpha' from vertical.
  • incident unpolarized light may interact with different structural elements of the skin since varying the angle of incidence affects the depth of penetration.
  • the angle alpha may be changed by changing the position of the light source, either manually, through a remote control, through a user interface 102, and the like.
  • the diffuse emission occurs because there is scattering and absorption that occurs from light bouncing around in the substructures.
  • the polarization of the light may be due to classical / quantum effects of skin structures interacting water. That is, skin structures possess enough of a magnetic and electric field to be able to alter the polarization of light as it strikes the structures and to affect the wavelength of light as it strikes the structures.
  • An aspect of the polarization of the reflected or re-emitted light may correlate with various measures associated with the particular skin structures targeted, and ultimately, a skin state 158.
  • a lesion present in a particular skin structure may cause the diffusion of a portion of the reflected or re-emitted light resulting in reflected or re-emitted light that is partially polarized and partially diffused.
  • collagen structures are one indicator of a biological difference between a benign and a malignant melanocytic skin lesion.
  • the collagenous differences may affect the polarization state of reflected or re-emitted light, and the resultant images may indicate locations of tumor center and tumor periphery. Such images may aid a practitioner in visualizing excision margins, as will be further described herein. Because melanocytes are located at the lower part of the epidermis, the appropriate wavelength may be selected for this depth as well as for the chromophores within the various types of nevi.
  • incident light is polarized
  • unpolarized incident light may reveal both the electrical and magnetic properties of skin.
  • the data sets generated may be of less value as compared to the data sets captured using incident unpolarized light, such as white light, a monochromatic light, light of multiple single wavelengths, and the like.
  • the wavelength and/or intensity of the incident light may be modified in order to measure the presence of specific molecules, such as collagen, elastin, cadherin, hemoglobin, and the like. Certain molecules possess the property of endogenous fluorescence. For example, if incident light is limited to a particular wavelength, such as 325 nm, collagen may be detected at an emission wavelength of 400 nm and 405 nm. Table 1 lists certain illustrative examples of excitation and emission maxima of biological molecules that exhibit endogenous fluorescence, such as amino acids, structural proteins, enzymes and coenzymes, vitamins and vitamin derivates, lipids, porphyrins, and the like.
  • a user may shine a light of a specified wavelength, such as and without limitation those shown in the excitation maxima column, onto the skin and collect reflected or re-emitted light to identify the presence of specific emission wavelengths in the reflections. It may be understood by one knowledgeable in the art that many different single wavelengths and combinations of wavelengths of light may be used to illuminate the skin.
  • a specified wavelength such as and without limitation those shown in the excitation maxima column
  • FAD flavin adenine dinucleotide
  • NADH reduced nicotinamide adenine dinucleotide
  • AND(P)H reduced nicotinamide adenine dinucleotide phosphate.
  • light may be emitted at any wavelength, such as across the range from 280 nm to 3800 nm.
  • Incident light may be blue, yellow, orange, red, or some other light.
  • the light source may be integral to the device 108 or provided from an associated source.
  • the light source may be a light-emitting or laser diode (LED) of any wavelength, such as and without limitation 280, 340, 360, 385, 405, 395, 400, or 480 nm incident excitation wavelengths, as well as infrared and near-infrared. Wavelengths in the ultraviolet and infrared ranges may also be emitted by the device 108.
  • the light source may be diffusion light, white light, monochromatic light, light of multiple single wavelengths, incandescent, electroluminescent, fluorescent, halogen, ultraviolet, polarized light, collimated light, light provided by a wireless communications device, light provided by a fiber optic cable, and the like.
  • the light source may comprise a diffuser to provide diffuse incident light.
  • a sensor for detecting reflected or re-emitted light from the skin may be embodied in optics resident in a CCD camera, CMOS-based imaging system, digital camera, webcam, camera embedded in a communications device such as a cell phone or iPhone, PDA (Personal Digital Assistant), a watch or other wearable device for continuous monitoring of the skin as in a sports-type indication, a third party device, a scanner, and the like.
  • the sensor may be adapted to absorb any wavelength of light, such as near IR or visible wavelengths.
  • the sensor may be adapted to automatically filter out particular wavelengths.
  • the sensor may be adapted to image any size area, such as a small portion of the skin, the full face, a complete cutaneous examination, and the like.
  • the sensor may be adapted to operate without any intervening fluids between the device 108 and the area of concern, or may be used with an oil-like application or other reflective media to the area of concern.
  • the sensor may be adapted to detect reflected or re-emitted light, from any distance from the area or when in contact with the area of concern, which may be used for subsequent visual and/or algorithmic analysis.
  • the images generated from this reflected or re-emitted light may be considered both visual as well as spectroscopically resolved images or electromagnetic skin maps.
  • the sensor may have an internal calibration scale that enables measuring the size of the region being imaged as well as the distance from the imaged area.
  • a lens may focus the reflected or re-emitted light from the detection optics onto a visible-NIR sensitive CCD, CMOS, or other sensory device.
  • the sensor may be adapted to acquire images at a high frame rate.
  • the device may possess a high magnification lens.
  • the device 108 may store captured images for analysis and/or transmittal to an analysis facility 154.
  • the analysis facility 154 may be a practitioner, an automated analysis tool, a practitioner employing analysis tools, and the like.
  • Data storage 1 10 may occur manually when image capture is initiated, may occur automatically upon contact with the skin, may be remotely controlled, and the like.
  • Data may be stored in an internal device memory 168 or may be stored externally in memory media 170 such as USB memory, an external hard drive, a mass storage device, and the like.
  • the device may be able to connect externally, either through a wired connection or wirelessly, to a computer, such as a laptop, kiosk, desktop computer, central server, and the like.
  • the connection may be a direct USB connection.
  • captured data may be downloaded or transmitted either automatically or upon manual initiation from the device 108 to the computer.
  • the device 108 may have a cradle in connection with a computer. When the device 108 is placed in the cradle, data may be transmitted or downloaded from the device 108. Additionally, the device 108 may receive software updates when connected to the computer, such as through the cradle.
  • the device 108 may have no internal storage and may only be able to transmit or store data externally through a persistent hard-wired or wireless connection. Data transmittal and storage may be a fully automated process or may be manually operated.
  • Data may be transmitted over a wireless network connection, a cellular connection, a wired connection, a Bluetooth connection, and the like. Data transmittal from the device 108 may enable remote assessment techniques.
  • non-image data may also be stored and/or transmitted by the device 108 as described herein, such as voice responses, text responses, video data, and the like.
  • the device 108 may have an internal microphone to record audio, a video camera to record video, a keyboard input to record text responses, and the like. In an embodiment, the device 108 may use externally available audio and video.
  • data storage may be in a skin health record 121.
  • the skin health record 121 may be an object or database or repository for an individual that contains information on key medical, non-medical, and cosmetic indications related to a user's skin. This may comprise images, graphics, icons, written history, personal demographic information, levels of cosmetic conditions such as moisture, elasticity, firmness, texture, color level, or non-medical conditions such as inflammation, and the like.
  • a user may self-populate the record 121 with data from any device 108, 109 or input 1 12.
  • the record 121 may contain a history of skin concerns, comments, a user blog, and the like.
  • the skin health record 121 may auto-populate upon acquisition of an image. For example, when a user submits their first image for analysis, a record 121 may be automatically created and populated with information, which may be edited, derived from the image and its analysis.
  • data storage 1 10 may occur in a practitioner record 180.
  • a practitioner record 180 may be a repository of key health characteristics including background demographic data, personal information, information on diet, skin health record 121 and the like. It may have embedded images, links to other image data files, tracking effectiveness of personal skin products, medical products, and OTC products and the like and their historical impact on key parameters. It may also capture community data or data of selected individuals who may be similar to the patient or user and may include rankings and comments and the like
  • data storage 1 10 may be in a personalized manufacturing record 172.
  • product ingredients to obtain a desired effect to make the skin healthy may be selected. This ingredient selection may be achieved by analyzing and tracking the change of various skin health parameters through the application of various products and ingredients through using the device 108 and tracking the change of the skin health over time through a personalized manufacturing record 172. Once the selected product ingredients are identified, they may be mixed to create a product best suited for the individual's skin characteristics and/or desired goals (such as improved moisturization). Thus a personalized product may be developed for the user. Additionally, this same process could be used for creation of specific customized skin products and ingredients for medical and non-medical purposes and conditions.
  • the form of the data captured may be compatible with any standard image processing and manipulation software and techniques, word processing software, slideshow presentation, spreadsheet applications, and the like.
  • the captured data may be in any suitable image format, such as jpeg, tiff, pict, png, bmp, gif, pdf, and the like.
  • multiple images may be captured as a movie or a movie may be constructed from combining multiple images.
  • the device 108 may be powered by any suitable source, such as an electric power plug, a battery, solar power, USB power, and the like.
  • a user may initiate power to the device 108 in order to begin acquiring images. Acquisition may commence automatically, may commence when the device 108 is placed against the skin, may commence when a trigger, such as a button, is actuated by a user, and the like.
  • the device 108 may have a display for viewing the area to be imaged. For example, a user may use the display with positioning tools to obtain exact images over time, such as a series of images taken over different days.
  • the display may be integral to the device 108 or may be a separate display.
  • the device 108 may be connected to a monitor, such as that of a computer, using a wired connection or a wireless connection.
  • a user interface 102 to the device 108 may display a real time view of the imaging.
  • the positioning tools may enable tracking and targeting.
  • a method of tracking and targeting is depicted.
  • the positioning tools may be used to track and store movement parameters of the imaging device 108 moving over a subject area.
  • the device may capture an image of the subject area at a plurality of locations.
  • the device 108 may identify a direction of movement of the imaging device 108 using an image processing technique for at least one captured frame.
  • the image processing technique may recognize the direction of movement of the imaging device by comparing each frame with at least three distinct features captured to thereby triangulate a location of the imaging device, as shown in Fig. 55.
  • the data of the captured image may be compared with a predetermined image database to store the image of the subject area and to store placement parameters of the imaging device 108. If no entry exists in the database, a new entry may be made.
  • the step of capturing the image of the subject area at a plurality of locations may include a sub-step of capturing a continuous video image of the subject area.
  • the step of capturing the image of the subject area at a plurality of locations may include a sub-step of capturing a frame by frame sequence of images of the subject area.
  • the step of identifying a direction of movement of the imaging device using an image processing technique may include a sub-step of a frame by frame comparison of the captured image to identify movement parameters of the imaging device.
  • the step of recognizing the direction of movement of the imaging device by comparing each frame with at least three distinct features captured to triangulate a location of the imaging device may include a sub-step of capturing a direction of movement of the imaging device by comparing three or more distinct positions across different frames.
  • the positioning tools may be an automated location tracking and data storage system for the imaging device 108, including an image capturing unit, a positioning unit coupled to the image capturing unit for positioning the imaging device on a subject area, and an image processing unit for enabling a frame by frame comparison of the captured image and for enabling the imaging device to capture three or more distinct points to triangulate a location of the imaging device to identify a direction of movement of the imaging device.
  • the image capturing unit may include a digital camera.
  • the image capturing unit may include at least one of a mobile device and a Personal Digital Assistant (PDA).
  • the image processing unit may include a comparison unit for comparing positions of three or more distinct points across different frames to capture direction of movement of the imaging device.
  • the automated location tracking and data storage system may further include a sub-system for measuring lateral motion of the image capturing unit from a predetermined point to a new location on the subject area.
  • the device 108 may have security features in order to protect the privacy of user data.
  • the device 108 may have a unique MacID with encryption technology.
  • the device 108 may be associated with peripherals or other functional attachments.
  • the device 108 may be associated with a blood pressure monitor or sensor, a heart rate monitor or sensor, and the like.
  • the device 108 may be used to perform a pre- diagnosis 162 of a skin lesion while also monitoring other endpoints such as blood pressure, heart rate, and the like in order to assess other aspects of health in addition to skin health.
  • the device 108 may be sized to permit a user to operate the device 108 in a handheld fashion.
  • the device 108 may sized for portability.
  • the device 108 may adapted for single- handed operation.
  • the device may be embodied as in Fig.
  • the illumination source is visible as a ring of LED's around a central detection area.
  • the size, handheld nature, and portability are clearly demonstrated.
  • the ease of operation enables even an inexperienced user, such as a home user connected to a laptop, to employ the device 108.
  • the device 108 may be a self- contained unit and not part of a larger camera system. In an embodiment, the device 108 may be designed for one handed ergonomic holding.
  • the device 108 may be used with or without application of reflective media. In an embodiment, the device 108 may be used to capture images at a distance, close-up, in direct contact, and the like. For example, software loaded on a computer interfaced with the device 108 may prompt for near distance and far distance image capture.
  • the device 108 may also be a standalone, non-hand-held version, which may be used to take images or particular body components or materials.
  • the device may be a miniature one, enabling portability and hand-held use. Some embodiments of the skin care device may be in the form of a handheld and portable wand that can be conveniently moved across a skin region to be examined. Some other embodiments of the skin care device may be so miniaturized that no dimension of the skin care device exceeds six inches. Such skin care devices may be embedded in wearable accessories, for example, bracelets, necklaces, ear-rings, and the like. Some embodiments of the skin care device may have a convenient user interface and/ or a display surface. In some embodiments of the skin care device, the device may be coupled to or embedded in a vertical display panel, for example but not limited to, a mirror, an LCD screen, a plasma screen, and the like.
  • the skin care device 4700 may include an electromagnetic radiation source 4702, a radiation detector 4704, and a skin condition analysis module 4708.
  • the electromagnetic radiation source 4702 may be capable of directing incident electromagnetic radiation to one or more locations on the skin of a person.
  • the radiation source 4702 may be a set of light emitting diodes (LEDs).
  • the incident radiation emitted by the radiation source 4702 may include radiation in the visible, near-infrared (NIR) and near-ultraviolet (NUV) spectrum.
  • the incident radiation may include white light.
  • the electromagnetic radiation source 4702 may be coupled to the radiation detector 4704.
  • the radiation detector 4704 may be capable of detecting the radiation re-emitted from the location and measuring various radiation parameters of the re-emitted radiation.
  • the radiation detector 4704 may be coupled to the skin condition analysis module 4708.
  • a variety of radiation parameters may be detected by the radiation detector, including, for example but not limited to, degree of polarization, intensity of the radiation at different wave-lengths, and the like.
  • the electromagnetic radiation sources, radiation detectors, and the skin condition analysis module have been previously described herein.
  • the skin condition analysis module 4708 may be capable of analyzing the radiation parameters of the reflected radiation and other information to generate a skin condition assessment.
  • the skin condition analysis module 4708 may be adapted to generate the skin condition assessment in real-time.
  • the radiation detector 4704 measures diffused reflectance.
  • the incident radiation may be white light and the radiation detector 4704 may measure the red, green, and blue components of the re-emitted light.
  • the skin condition assessment may also be partly based on analysis of a photographic image of the skin location.
  • the term "diffused reflectance” may refer to radiation, sometimes loosely referred to as light, scattered in many directions from target samples. Diffused reflectance is the complement to specular, or mirror-like, reflection. If a surface is completely non-specular, the reflected or re-emitted light will be evenly spread over the hemisphere surrounding the surface. Diffused reflectance stems from tiny irregularities on surfaces of targets and is the reflection of incident light from uneven or granular surfaces of targets such that incident light strikes the targets and is scattered over wide angles.
  • Some embodiments of the skin care device may have a memory module for storing the skin condition assessments and other data, such as with timestamps. Some embodiments of the skin care device may have a communication module for communicating the skin condition assessments and other data with timestamps to a remote computer. The communication of data may occur, for example, over a wire, wirelessly, using an internet, and the like. The skin condition assessments and other data may also be accessed in remote locations via mobile devices and/or computers. Such remote access may be particularly convenient for service providers, such as for example, dermatologists.
  • the skin care device may have a user interface to enable a user to interact with the skin care device.
  • the user interface may enable a user to give instructions to the device, for example, to analyze the available information to generate a real-time skin condition assessment of a skin location or a larger skin region.
  • the user interface may be voice-operated providing the facility to give commands to the skin care device through speech commands.
  • GUI graphical user interface
  • WUI web-based user interface
  • command line interface touch interface
  • touch interface any combination of the above.
  • the user interface may also provide alerts to a user if any abnormal skin condition, such as for example, a clogged pore, is detected.
  • the alerts may be in the form of a light signal, a beep, an email alert, an SMS alert, and the like.
  • the skin care device may have also have a display surface either for a more convenient and intuitive user interface and/or for viewing an image of a skin region and/or for viewing some useful skin-related information, for example, a skin condition assessment report, a skin regimen recommendation report, and/or a skin regimen effectiveness report.
  • the display surface and/or the user interface may be touch-sensitive to enable touch-control of the device.
  • the skin condition assessment data of locations may be overlaid on an image of a larger skin region displayed on the display surface, providing a useful picture of the health of the entire skin region in a single view.
  • Some embodiments of the skin care device may also have an access restriction module restricting access to patient data to authorized users only.
  • the access restriction module may be based on a user name and password feature and/or biometric access control, for example, fingerprint recognition, facial recognition, retina recognition, and the like.
  • the skin condition analysis module 4708 may have access to user information like age, gender, ethnic group, and the like, and such information may be used to build a user profile and used in analysis of the skin condition.
  • the skin care device 4700 may be used in a user's home, a user's bathroom, a cosmetic store, a provider's office, a mobile location, and the like.
  • the skin care device 4700 may be used at any time of the day, such as before going to bed, before or after using a cleanser on the skin, and the like.
  • the skin care device 4700 may have a skin care regimen recommendation module 4710 capable of generating a displayable skin care regimen recommendation.
  • the skin care regimen recommendation may include information not only about the most appropriate skin-care products, but also information about the best way of applying the product, the timing, amount, and frequency of application, and the like.
  • the skin care regimen recommendation module 4710 may be linked to the skin condition analysis module 4708 so that the skin care regimen recommendation is personalized to the skin condition of each person.
  • the skin care regimen recommendation may be generated in real-time based on skin condition assessments generated by the skin condition analysis module 4708, product information, and other relevant information analyzed using algorithms, as described herein.
  • the skin care regimen recommendations generated by the skin care regimen recommendation module 4710 may be displayed to the user in real-time, for example, on a display surface attached with the skin care device 4700.
  • the skin care regimen recommendations generated by the skin care regimen recommendation module 4710 are based at least partly on determination of a skin profile, or skin state 158, of the user and use of skin care regimen recommendations of persons with a similar profile.
  • the skin care regimen recommendation module 4710 is coupled to a skin-care product database 190. If the products recommended by the skin care regimen recommendation module 4710 are available in the product database 190, the user may be informed and given an option to purchase the product immediately. In some embodiments, the user may operate the skin care device 4700 in a point-of-sale location, for example, a retail store, and the availability of a product recommended by the skin care regimen recommendation module 4710 may be indicated by an audio-visual signal, such as for example by lighting up the shelf in which the product is located.
  • a user practicing a specific skin care regimen may be interested in tracking the effectiveness of the skin care regimen over a period of time.
  • the skin care device 4700 may have a skin care regimen effectiveness module 4712.
  • the skin care regimen effectiveness module 4712 may be coupled with the skin condition analysis module 4708.
  • the skin condition of the user may be tracked at different points of time using the skin care device 4700 and may be displayed to the user on a display surface.
  • the device could also help track changes by various activities - exercise, food, smoking, work, and the like.
  • Fig. 48 shows an embodiment of a skin care device 4700 in which the skin care device is wand- shaped.
  • a user may switch on the wand-shaped device 4800 and move the device over her face.
  • the wand-shaped device may have a grip 4802, a radiation detector 4808, an indicator 4804 that may provide an indication such as with light, warmth, sound, and the like, an LED light 4810, and a power source 4812.
  • the wand-shaped device 4800 is functionally similar to the skin care device 4700 described earlier.
  • the wand-shaped device 4800 may comprise an electromagnetic radiation source, a radiation detector, and a skin condition analysis module.
  • the wand-shaped device 4800 may be miniature, handheld, and portable.
  • the electromagnetic radiation source may be one or more LEDs. Each of the LEDs may have unique predetermined frequencies. In some embodiments, the one or more LEDs may be arranged in a line to form a light strip.
  • the wand-shaped device 4800 may be powered via a USB coupled to an external power source or through built-in batteries, or other similar power source.
  • the radiation detector 4704 detects re-emitted light and sends information back to the skin condition analysis module 4708.
  • the module 4708 employs an algorithm for skin condition analysis.
  • Fig. 49 shows another embodiment of a vertical panel-including skin care device 4900, in which the skin care device comprises an electromagnetic radiation source 4702, a radiation detector 4704, a skin condition analysis module 4708, a user interface 4714, and a vertical display panel 4902.
  • the skin care device comprises an electromagnetic radiation source 4702, a radiation detector 4704, a skin condition analysis module 4708, a user interface 4714, and a vertical display panel 4902.
  • the vertical display panel 4902 may have the user interface 4714 on the sides of the vertical display panel 4902.
  • the display panel may be touch-sensitive and in such cases, the vertical panel itself may be part of the user interface.
  • An image of a skin region may be displayed in the display panel.
  • a user may touch a location on an image and this may trigger display of a magnified image either on the display panel or on another screen.
  • a menu bar may show up in the user interface 4714, and the user may be able to view various reports, for example, a skin condition assessment report, a skin regimen recommendation report, a skin regimen effectiveness tracking report, and the like.
  • the user interface 4714 may enable a user to give instructions to the device, for example, to analyze the available information to generate a real-time skin condition assessment of a skin location or a larger skin region.
  • the user interface may be voice-operated providing the facility to give commands to the skin care device 4900 through normal speech commands.
  • GUI graphical user interface
  • WUI web-based user interface
  • command line interface touch interface
  • the electromagnetic radiation source 4702 is capable of directing incident electromagnetic radiation to one or more locations on the skin of a person.
  • the radiation source 4702 may be a set of light emitting diodes (LEDs).
  • the incident radiation emitted by the radiation source 4702 may include radiation in the visible, near-infrared (NIR) and near-ultraviolet (NUV) spectrum.
  • the incident radiation may include white light.
  • the electromagnetic radiation source 4702 may be coupled to the radiation detector 4704.
  • a variety of radiation parameters may be detected by the radiation detector 4704, including, for example but not limited to, degree of polarization, intensity of the radiation at different wavelengths, and the like.
  • the skin condition assessment may also be partly based on analysis of a photographic image of the skin location.
  • Some embodiments of the vertical panel-including skin care device may have a memory module for storing the skin condition assessments and other data, such as with timestamps.
  • Some embodiments of the vertical panel-including skin care device may have a communication module for communicating the skin condition assessments and other data with timestamps to a remote computer.
  • the communication of data may occur, for example but not limited to, over a wire, wirelessly, using an internet, and the like.
  • the skin condition assessments and other data may also be accessed in remote locations via mobile devices and/or computers. Such remote access may be particularly convenient for service providers, such as for example, dermatologists.
  • the user interface 4714 may also provide alerts to a user if any abnormal skin condition (for example, a clogged pore) is detected.
  • the alerts may be in the form of a light signal, a beep, an email alert, an SMS alert, etc.
  • There may be other methods e.g. a small electric tingle, a mark, a sound, and a light, a heat emitting signal, etc. to alert users about skin conditions requiring user attention.
  • the skin condition assessment data of locations may be overlaid on an image of a larger skin region displayed on the vertical display panel 4902, providing a useful picture of the health of the entire skin region in a single view.
  • the vertical panel-including skin care device may also have an access restriction module restricting access to private information to authorized users only.
  • the access restriction module may be based on a user name and password feature and/or biometric access control, for example, fingerprint recognition, facial recognition, retina recognition, and the like.
  • the skin condition analysis module 4708 may have access to user information like age, gender, ethnic group, and the like, and such information may be used to build a user profile and used in analysis of the skin condition.
  • the vertical panel-including skin care device 4900 may be used in a consumer's home, a consumer's bathroom, a cosmetic store, a provider's office and/or a mobile location.
  • the vertical panel- including skin care device 4900 may be used at any time of the day, such as before going to bed, before or after using a cleanser on the skin.
  • the device may include or be coupled with a skin care regimen recommendation module capable of generating a displayable skin care regimen recommendation.
  • the device may include or be coupled with a skin care regimen effectiveness module capable of generating a displayable skin care regimen effectiveness report.
  • the vertical display panel is a mirror.
  • the vertical display panel is an LCD panel or a plasma screen.
  • the device also includes or is coupled with a camera for taking photographic images of a skin region.
  • the camera is integrally attached to the display surface or display panel. In certain other embodiments, the camera is either wired to the display surface or display panel. In other embodiments, the camera is wirelessly coupled to the display surface or display panel.
  • the user interface 4714 may have one or more buttons (not shown explicitly) for doing a skin scan and/or analysis.
  • the buttons may be of different types, for example push buttons, hard wired buttons, or a combination of both.
  • the user may touch a button on the display panel for doing a skin scan, while she may touch another button for directing the machine to do a skin analysis.
  • Fig. 50 shows an embodiment of a wearable skin care device 5000, in which the device is in the form of a wearable device.
  • the wearable device can be worn by a user in the form of necklace, ear-rings, bracelets, a patch, or as a sensor attached to a strap, and the like.
  • Such wearable devices can be persistent, personalized skin care monitors.
  • the wearable skincare device 5000 is functionally similar to the skin care device 4700 described earlier. Similar to the skin care device 4700, the wearable skincare device 5000 comprises an electromagnetic radiation source, a radiation detector, and a skin condition analysis module. Preferably, the wearable skincare device 5000 is miniature, hand-held, and portable, and no dimension of the device exceeds six inches. [00397] In some embodiments of the wearable skincare device, the electromagnetic radiation source may be one or more LEDs. Each of the LEDs may have unique predetermined frequencies. In some embodiments, the one or more LEDs may be arranged in a line to form a light strip.
  • the wearable skincare device 5000 may be powered via a USB coupled to an external power source or through built-in batteries, motion power, solar power, or other similar power source
  • Embodiments of the wearable skincare device may also have sensors for measuring various body and environmental parameters.
  • body parameters that could be measured by the wearable skincare device are body temperature, hemoglobin antioxidant level, etc.
  • environmental parameters that could be measured by the wearable skincare device are air cleanliness, humidity, temperature, UV index, external air quality, smoke index, and the like.
  • the device 108 may be adapted for use as a component of a minimally invasive medical device associated with laparoscopy, cytoscopy, ureteroscopy, arthroscopy, endoscopy, dermoscopy, gynecology, urology, dentistry, natural orifice insertion analysis such as through ears, mouth, anus, nose, and external breast cancer analysis through the skin, and the like.
  • the system may be able to process the data and to appear on a video monitor or other display in a surgical suite or other medical setting.
  • a medical professional may be able to select a viewing mode, such as still image capture or video capture, and may be able to manually adjust the parameters of the light source, sensor and display to assist in observation, identification, and monitoring with the device 108.
  • the system may be pre-programmed with various protocols for the various types of medical procedures and tissues types that a medical professional may encounter such that the system may automatically handle the device 108 based on the medical professional's indication of the type of procedure and tissue being examined.
  • the device 108 may be used as part of a system and method for distinguishing between healthy and suspect tissue in real or near-real time on a patient.
  • the imaging device 108 allows a surgeon or other practitioner to precisely determine the border area around a surgical intervention for primary cutaneous melanoma, skin cancers, and other skin diseases that require excision around the skin.
  • the surgical excision of suspect tissue such as cutaneous melanoma
  • the device 108 allows an automatic determination of the excision margin for primary cutaneous melanoma based on the optical characteristics of the surrounding skin.
  • the device 108 and associated algorithms 150 and analysis techniques may be employed to image a particular site, and determine border area, suspect tissue, either before surgery, in pre-surgery, or during surgery.
  • the software could also show post surgical analysis of affected skin tissue. Using the device 108 allows more precise determination of the border area instead of relying on subjective experience or fixed tables as noted in medical journals and other published works.
  • a melanocytic lesion is displayed.
  • the visible melanoma 5602 or suspect tissue is surrounded by normal looking skin, but which may contain unhealthy /diseased tissue that must be excised 5604 (pseudo-normal skin 5604).
  • the device 108 may be able to visualize the border between healthy and non healthy tissue 5608, thereby allowing the surgeon to spare healthy tissue 5610 that should remain intact.
  • the device 108 may perform an estimation and provide an outlined area 5612 indicating where the surgeon should cut the tissue.
  • an embodiment of a user interface for visualizing a melanocytic lesion is displayed along with access to tools for analyzing an image of the lesion 5702, manually selecting a border 5704, automatically selecting a border 5708, drawing a border area 5710, and the like.
  • the device 108 may enable a skin health test 160.
  • the imaging device 108 may be used to perform a skin health test 160 to learn the characteristics of the skin and to obtain a diagnosis.
  • the hardware device may capture an image and enable analysis of the image.
  • the imaging components within the device 108 may enable measuring various skin health characteristics like color, age, damage, collagen, elastin, pores and types, keratin, and the like.
  • the skin health test 160 may be performed in the home, in a spa, clinic, hospital, from a mobile phone at any location, and the like.
  • the skin health test 160 may be used in conjunction with specific background information through questionnaires, image upload, genetic testing, DNA samples, and lifestyle habits to determine a skin state 158.
  • the test 160 would respond with specific information related to the biophysical health of the skin, a portion of which would be physical and genetic disposition to certain medical or non-medical or cosmetic problems or conditions.
  • the device 108 may enable a pre-diagnosis 162.
  • a practitioner such as the user, a dermatologist, medical practitioner, aesthetician, and the like
  • the user may submit a questionnaire and image with a pre-diagnosis of conditions prior to going to see a practitioner and allow a follow-up. Images captured by the device may be submitted to obtain a preliminary diagnosis to enable effectively referring the case to the best practitioner.
  • the pre-diagnosis 162 may be performed by software algorithms on the images, manual analysis, a combination thereof, and the like.
  • the pre- diagnosis 162 may include the preliminary assessment as well as indicate the time required and the steps required for the final diagnosis or assessment. This pre-diagnosis 162 feature may enable effective scheduling of the practitioner.
  • the pre-diagnosis 162 could also help screen for particular skin issues as well as identify users with certain issues.
  • the device 108 may enable remote monitoring 164.
  • the user may use the device in the privacy of their home, work, or any other location to perform remote monitoring 164 and submit images to track progress of their skin's health or medical conditions.
  • a practitioner may be able to remotely guide changes in treatment or guide on prevention factors. Remote diagnosis may greatly increase efficiency of progress monitoring since users will not have to make a physician trip to the provider, and the provider could conveniently select a time during the day to observe the patients change.
  • the monitored data may be viewed as a recording or in real time.
  • the imaging device 108 may illuminate an area of concern at a known angle of incidence with unpolarized light.
  • the reflected polarized light which possesses the electrical properties of the area of concern, may be subtracted from any reflected diffusion light, which possesses electromagnetic properties of the area of concern.
  • the distribution of pixels in the image corresponding to the diffusion light and reflected polarized light may be determined and indicated by any conventional means.
  • a one-to-one mapping of pixel image distribution between the diffusion light image, corresponding to an electromagnetic signal, and reflected polarized light, corresponding to an electrical signal image may be made with a distribution of the intensity of the spectroscopic data for the same area.
  • a magnetic gradient image of the area may be made by equipment such as an AFM-MMR (Atomic Force Microscopy in Magnetic Mode Regime) and from the one-to-one correspondence, a skin state 158 may be based on the gradient image, diffusion light image, and reflected polarized light image.
  • AFM-MMR Atomic Force Microscopy in Magnetic Mode Regime
  • the device 108 may be an imaging device 108 for performing digital spectroscopic imaging of the skin.
  • Incident unpolarized light may be delivered, either vertically or on an angle alpha from vertical, from an unpolarized light source associated with the device 108, such as a white light, diffuse light, monochromatic light, light of multiple single wavelengths, and the like, to a target skin structure.
  • White light which possesses both electrical and magnetic properties, when incident onto a skin structure at a particular angle interacts with the structure's components and leads to the reflected or re-emitted light having a polarized light component.
  • the incident light may be polarized. Unpolarized light reflected by skin structures may become polarized, at least in part.
  • the reflected or re- emitted light may be captured by the device 108.
  • Such multispectral skin imaging may be used to develop an electromagnetic skin topography.
  • aspects of the polarization of the reflected or re-emitted light such as an orientation, an amplitude, a phase, an angle, a shape, a degree, and an amount, and the wavelength of the reflected or re-emitted light
  • the biophysical properties of skin structures may be obtained.
  • a skin state 158 may be determined from the aggregate biophysical data obtained from one or more skin structures as well as a visual analysis of the captured images and any additional data obtained from the user anecdotally.
  • the skin state 158 may encompass data on moisture, wrinkles, pores, elasticity, luminosity, and any of a number of measures, as described herein.
  • the angle of incident white light the depth of penetration of the light to skin structures may be varied. Each depth within the skin corresponds to different skin structures. For each skin structure or depth, there may be a specific angle which produces a full polarized reflection. For example, a certain angle of incidence may be used to obtain data for skin structures within the epidermis, however, the angle of incidence may need to be changed in order to obtain data on skin structures within the subcutis which resides at a different depth within the skin.
  • the angle of incidence may be modified to penetrate the skin anywhere from a few microns up to a few centimeters, thus enabling the capture of reflections from other non-dermal structures.
  • the device 108 may be used as a non-invasive imaging tool, such as to image tumors, breast cancer, melanoma, and the like.
  • the area to be imaged may be any biological tissue that may have normal or pathologic variations in its structure, such as variations in the tissue's birefringent properties. For example, scars, keloids, hypertrophic scars, and stria all have organizations of collagen fibers that are different from normal skin. Since collagen is a primary determinant of cutaneous wound repair, it may be of interest to monitor changes in collagen structure and concentration.
  • the stage of healing may be determined by the size of collagen bundles which may increase as healing progresses, by the organization of collagen structures at the molecular or small-fibril level which may increase as healing progresses, by the return or increase of birefringence, and the like. Since collagen structures are polarization-sensitive, changes that occur in the structures may be monitored using a polarization-based technique during scar formation, the healing process, and treatment of scars, as has been and will be further described herein.
  • Being able to measure the electrical and magnetic properties of various skin structures may enable the differentiation between healthy and non-healthy skin structures.
  • Normal or healthy skin structures exhibit a unique conformation that differs from the conformation exhibited by equivalent structures when unhealthy or abnormal.
  • These conformational changes can be detected by differences in an aspect of the light reflected off of skin, re-emitted light, or amount of absorption in the skin, such as an aspect of the polarization of the reflected or re-emitted light.
  • the aspect of polarization may be the wavelength of the light, an orientation, an amplitude, a phase, an angle, a shape, a degree, an amount of polarization of the light, and the like.
  • light can be described as comprising an electric field and a magnetic field which can be described as two vectors, E and B, which behave as waves.
  • the vectors are perpendicular to the propagation direction of the light, and they are orthogonal to each other.
  • E the electric field
  • B can be determined via Maxwell's equations, and vice versa.
  • the magnetic component or the degree of polarization/polarization state may be determined.
  • the light may spread to other wavelengths that can be measured.
  • the polarization state of the reflected or re-emitted light may be described by a number of parameters.
  • the polarization state may be described in terms of the polarization ellipse, specifically its orientation and elongation.
  • Parameters which may be used to describe the polarization state may include the azimuth angle ( ⁇ ) which is the angle between the major semi-axis of the ellipse and the x-axis, the ellipticity ( ⁇ ) which is the ratio of the two semi-axes, the ellipticity angle which is the arctangent of the ellipticity, the eccentricity, the amplitude and phase of oscillations in two components of the electric field vector in the plane of polarization, and the like.
  • an ellipticity of zero corresponds to linear polarization and an ellipticity of 1 corresponds to circular polarization.
  • the polarization of the reflected or re-emitted light may be at least one of elliptical, linear, circular, left-circular, right-circular and any potential combinations thereof.
  • determining a skin state 158 may comprise processing and analyzing 154 the reflected or re-emitted light to obtain images for visual and spectroscopic analysis. Analysis 154 may be facilitated by examining the wavelength and other characteristics of the reflected or re-emitted light. For example, if the incident light is white light, the reflected or re-emitted light may be filtered to examine a collection of wavelengths or a single wavelength and, ultimately, a specific skin structure fluorescence. In another example, monochromatic or semi-monochromatic light, such as provided by an LED may be used to excite targeted fluorophores and chromophores. In this example, fluorescence of deeper layers may be extracted.
  • the reflected or re-emitted light in this example may also be filtered to isolate a specific fluorescence.
  • varying the wavelength of the illuminating light may enable detection of biophysical properties from various depths within the skin.
  • certain chromophores such as the various forms of hemoglobin found in blood, have specific absorption bands; thus processing of data created with different color light may yield information about chromophore distribution that may be polarization-sensitive.
  • the wavelength dependence may be obtained in several ways: 1 ) illuminate sequentially with light of a single wavelength or multiple single wavelengths and collect each resultant image separately; or 2) illuminate with white light and examine the reflected or re-emitted light for individual wavelengths or a collection of individual wavelengths either during detection or during processing.
  • Algorithms 150 may be used to obtain information from data obtained by either method by processing and analyzing one or more wavelengths of light to form a spectroscopic, polarization-based image.
  • the combination of both techniques may enable the elimination of the reflection from the surface of the skin.
  • filtering may be employed to filter out a range of wavelengths, such as those belonging to the ultraviolet, infrared, near infrared, visible, and the like.
  • the filter may be a digital or an analog filter.
  • captured images may be processed by software that may be able to employ digital filter techniques to process the images for analysis.
  • any digital filter parameter may be selected such as a particular cutoff wavelength, a set of single wavelengths, a sampling interval, and the like.
  • a digital filter may be used to isolate reflections of 405, 458, 488, 532, 580, and 633 nm wavelengths.
  • an analog filter may be employed to filter the images as they are captured, such as a filter that is integral to the optics of the device 108, or as they are stored, transmitted, manipulated, processed, and the like, such as with an external analog filter.
  • Filtering the images may result in obtaining images of underlying structures and/or a specific pattern of polarization. Filtering the images may result in the separation of the electrical and magnetic components of the reflected or re-emitted light. Filtered images may be subjected to algorithmic analysis. Filtering may eliminate reflections due to skin surface reflections by isolating specific wavelengths of light.
  • sebaceous glands may appear as bright spots in an image when only a certain wavelength of light is isolated for analysis, while isolation of a different wavelength of light enables the visualization of all the pores in the imaged area.
  • the fluorescence from deeper layers may be isolated.
  • Image processing may be used to count and measure changes in the sebaceous glands and pores, including count, size, activity of gland, quantity of sebum/other materials inside the sebaceous gland, quantity of sebum/other materials inside the pore, age of the contents within the gland, age of contents within the pore, amount of inflammatory processes surrounding the gland, and the like. Multiple images from different image sources may be combined for the analysis.
  • a host system 104 may comprise algorithms 150, data integration 152, analysis tools/ API's 154, a skin state 158, an expert consult 128, and the like.
  • the skin state 158 may be a data object or characterization of skin based on tests 160, pre-diagnoses 162, and monitoring 164 performed by a device 108, user input, expert consult 128, other inputs 1 12, analysis 154, algorithms 150, and the like.
  • the skin state 158 along with all of the underlying data and user information may be stored in a skin health record 121.
  • the host system 104 may comprise server architecture.
  • the host system may be technology agnostic.
  • the host system 104 may comprise one or more cloud computing, service-oriented architecture, distributed objects, and the like.
  • expert consult 128 may provide analysis, recommendations, assessment advice, and the like.
  • the skin image data collected as well as the pre-diagnosis, in addition with any other allied data such as physician's diagnosis, insurance, blood analysis, and the like may be referred to an expert either by the user or a practitioner, or by other users to obtain an analysis, recommendation or assessment advice.
  • Experts could be located in geographically distant locations, and may have very different skills.
  • the skin image data and analysis may be shared at the request of another user with an herbal specialist in India, or the user may request the image data to be shared with an aging expert in France to learn of best suited skin care treatment from their experience.
  • the expert's consultation analysis may be maintained on the host system 104 as part of the skin history record 121 and may be accessed by the user at their convenience, or shared with other users.
  • the system 104 may be a home-based, in clinical or medical settings, at spas and salons, at a cosmetics counter and in cosmetics sales, and the like to perform skin analysis discretely and accurately in a low cost, rapid, and secure fashion.
  • the device 108 may integrate with a user interface 102, online platform 129, mobile platform 124 and the like to perform analysis 154, skin state 158 record keeping, obtain referrals/analysis from a remote practitioner or algorithm 150, and the like.
  • the home-based system 104 may allow a practitioner, who may be any qualified or unqualified person to give advice, to analyze cosmetic or non-cosmetic conditions that may be captured by an imaging device 108 or third party device 109 and give advice and recommendations on products, regimen, diet, lifestyle and the like based on inputs from questionnaires, uploaded images, and the like.
  • the system may consist of a starter website that may be customizable for a personal business where the practitioner could organize clients' cosmetic skin health, track their regimens, recommend products, be their online advisor, and the like. This would leverage the analysis and device platform to allow a practitioner to analyze comments, images, questions, and/or concerns and the like and give advice, consultation on lifestyle improvement and tracking.
  • a spa/ salon based system may enable personalized skin assets.
  • the spa may own the device, the device may capture images to feed a large scale display adapted to present a skin condition, and then a practitioner may be able to simulate the effect of treatment.
  • Users may compare a skin state 158 with peers or other spa goers and generate recommendations based on what worked for them or what they bought. Desired improvements may be correlated to ingredients and most effective products / regimens 1 18 for the users' skin.
  • the regimen 1 18 may be a feature that enables users to learn what product sequence would work best for their skin, based on a hardware-led personalized skin care assessment 122 and / or type determination 130 for the skin and product experience sharing via ranking and rating 138 and / or comments regarding product effectiveness and experience (e.g. smell, taste , feel, texture, color, etc.) collection.
  • the regimen 1 18 may be a dynamic recommendation based on users' collective inputs as well as experts' inputs on products that would best suit the user's individual needs.
  • the spa / salon based system 104 may generate product/ service recommendations based on a skin state 158, offer one-click shopping based on recommendations and enable SKU tracking, offer wellness packages such as through a contractual relationship, provide the ability to port regimen from spa to spa, from home to spa, and the like, enable optimization of regimens/ advising such as helping practitioners tailor the length of a procedure, enable development of targeted therapies, enable clear, visual communication to clients, generate effectiveness of products/services reports, and the like. Reports may be based on or comprise correlation with other users, feedback on regimen 118, modifications of a regimen 1 18, skin cycle monitoring, and the like.
  • a medical practitioner based system such as a dermatologist, general physician, metabolist, and the like, may enable pre-diagnosis, may link to the practitioner's scheduling system, may enable pre-pricing of services, may enable follow-up tracking, and the like.
  • a cosmetic sales or retail based system 104 may enable integration with inventory of product enabling clearing of inventory.
  • a handheld/portable device 108 may be used at a makeup counter, in a drugstore, at a home or trade makeup show/party, and the like. Users may purchase peripherals/accessories for the device, such as a holster, charger, and the like. Users may pay-per-scan or may have a subscription scanning service and the like.
  • the system 104 may be based in health clubs, gyms, resorts, and the like.
  • a cosmetics manufacturing / testing based system may enable skin state- based product design, targeting skin care samples to particular consumers, and the like.
  • the system 104 may be veterinarian based to monitor veterinary dermal- and non-dermal concerns.
  • the system 104 may be based in a hospital, ER, military setting, and the like to enable rapid assessment of medical conditions, triaging urgent skin care, and the like.
  • the system 104 may be agriculturally based to enable application to fruits, vegetables, and other such agricultural products.
  • the system 104 may be used in a battlefield scenario or in an austere environment, such as in space flight, air flight, underwater, submarine, and the like, to enable wound management, battlefield diagnosis and triage, and the like.
  • the system 104 may be research based to enable comparing any materials and their specific composition. Based on using the reading of the electrical property of the light, a user may be able to determine a similarity or difference between imaged material.
  • determining a skin state 158 may comprise employing an analysis 154.
  • the acquired data may be analyzed by a practitioner, such as a physician, dermatologist, spa employee, clinical trial practitioner, aesthetician, cosmetologist, nutritionist, cosmetic salesperson, and the like.
  • the practitioner may analyze the data upon acquisition, visually, with the assistance of an algorithm 150, expert consult 128, database 1 15, and the like.
  • the practitioner may be remote from the location of data acquisition.
  • an algorithm 150 may be used to process and analyze 154 the reflected or re-emitted light to obtain spectroscopically resolved images, either automatically or under the control of a user, practitioner, and the like.
  • an algorithm 150 may be used to generate an image of an area of concern using the difference between the reflected polarized light, which possesses the electrical properties of the area, and the reflected diffusion light, which possesses the electromagnetic properties of the area of concern.
  • Algorithms 150 may be rules-based software and processes to 1 ) analyze imaging evidence to obtain skin health, 2) correlate skin health with ingredients, medicaments, and/or products that may be best suited for the determined skin health, 3) correlate skin health with peers in a skin health community, and 4) recommend and design personalized products based on skin health and/or other like users usage experience, 5) observe measurable changes in skin health, and the like.
  • Algorithms 150 may be automated.
  • Algorithms 150 may be used to analyze 154 medical concerns, such as degree of suspicion of cancer, rash analysis, and the like. Algorithms 150 may be used to analyze 154 non-medical concerns, such as the effectiveness of a medical, non-medical, or cosmetic regimen 1 18, a pimple avoidance regimen 118, a sun-protection effectiveness, an itch prevention cream, and the like. Algorithms 150 may be useful for correlating desired improvements with ingredients and most effective products for improving or maintaining the user's skin health. The algorithm 150 may utilize a calibration scale to determine the skin structures imaged based on the angle of incidence, wavelength and intensity of the light source, an aspect of the reflected or re-emitted light, filter parameters, and the like.
  • Algorithms 150 may be useful for determining a dermascopic effect, a luminescence effect, a spectroscopic effect, and the like.
  • analysis 154 may comprise examining at least one of: physical data and/or an image of the material using diffusion white light; physical data and/or an image of material using light of a single wavelength or multiple single wavelengths; physical data and/or an image of the material using polarized, reflected or re-emitted light of a certain angle; physical data and/or an image of the material generated using the difference between diffusion white light and polarized reflected or re-emitted light of a certain angle; physical data and/or an image of the material generated using the difference between light of a single or multiple wavelengths and polarized, reflected or re-emitted light of a certain angle; and the like.
  • Algorithms 150 may be used with data and images generated by the device 108 or third party hardware 109. Algorithms 150 may be used with data and mages captured using any image capture device or technique, employing any kind of incident light, such as unpolarized light, polarized light, monochromatic light, diffuse light, white light, multiple single wavelength light, and the like. In embodiments, any captured data or image may be subjected to algorithmic analysis, as described herein.
  • the algorithm 150 may be based on artificial neural networks, non-linear regression, or fuzzy logic.
  • the algorithm 150 may be used in skin lesion diagnosis based on a probabilistic framework for classification. Two kinds of data may be inputs to the neural network or to non-linear regression: numerical data such as intensity, size, numbers, and the like, and descriptive data such as white, gray, dark, and the like. Fuzzy logic may directly encode structured descriptive data in a numerical framework.
  • neural and fuzzy machine intelligence may enable correspondence between input data taken from collected images and a biophysical skin state 158.
  • the algorithm 150 may be based on fractal and multi-fractal analysis of images based on biophysical and spatio-temporal data.
  • Both digital image data and spectroscopic data of skin may be analyzed using Hausdorff dimensions (fractal property) and Kolmogorov's entropy (K-entropy). Then, spectroscopic data may be divided into spatio-temporal cells and analyzed as multi-fractal objects, yielding information about a level of functional disharmony of skin structures (epidermal and dermal). Structural data of these two analyses can be correlated to determinate a one-to-one correspondence between them. Once fractal correlations between digital image data and spectroscopic data of skin are established, it may be possible to obtain information about a functional state of skin structures through multi-fractal analysis of digital image data.
  • an algorithm 150 may be for the analysis 154 of data integrity.
  • an algorithm 150 may be able to determine if the image has been captured in high enough detail to render subsequent analyses reliable.
  • an algorithm 150 may be useful for the analysis of skin characteristics, obtaining the biophysical properties of the skin, and determining a skin state 158.
  • the skin state 158 may capture a combination of underlying skin structure with time-based variance. Some variation may be predictable but some may be based on a transient condition like infection, sunburn, hormonal imbalance, and the like.
  • the algorithm 150 may be able to measure aspects such as the structure, form, concentration, number, size, state, stage, and the like of melanocytes/ melanin, hemoglobin, porphyrin, keratin, carotene, collagen, elastin, sebum, sebaceous gland activity, pores (sweat and sebaceous), wrinkles, moisture, elasticity, luminosity, all forms of the aforementioned, such as derivatives, salts, complexes, and the like.
  • the algorithm 150 may be used to make a quantitative assessment of clinical, medical, non-medical, and cosmetic indications, such as moisture level, firmness, fine lines, wrinkle count and stage, pore size, percent of open pores, skin elasticity, skin tension lines, spots, skin color, psoriasis, allergies, red areas, general skin disorders and infections, or other skin related concerns for the user such as tumors, sunburns, rashes, scratches, pimples, acne, insect bites, itches, bleeding, injury, inflammation, photodamage, pigmentation, tone, tattoos, percent burn/ burn classification, moles (naevi, nevus), aspects of skin lesions (structure, color, dimensions/asymmetry), melanoma, dermally observed disorders and cutaneous lesions, cellulite, boils, blistering diseases, management of congenital dermal syndromes, (sub)-cutaneous mycoses, melasma, vascular conditions, rosacea, spider veins, texture, skin ulcers, wound healing, post-operative tracking, mel
  • the algorithm 150 may also be useful for the analysis of and obtaining the physical properties and composition of hair, nails, biological substances, gaseous substances, food, wine, water, liquid, metal, non-metals, plastics, polymers, and the like. Either manually or as determined by an algorithm 150, a targeted wavelength or wavelengths may be employed for specific endpoint measurements.
  • Either a specific wavelength or multiple wavelengths may be chosen for the incident light or a specific wavelength or wavelengths may be isolated by filtering, as described herein.
  • An algorithm 150 may determine the presence, absence, structure, form, and the like of particular skin structures based on the properties of the reflected or re-emitted light. For example, an algorithm 150 may detect which axes/ angle the light is polarized on and compare this to signature emission spectra of individual proteins/ underlying skin structures. Each skin structure may have a unique signature pattern based on the electrical and magnetic contributions of molecule(s) present in the skin structure. The algorithms 150 may identify, analyze and separate the electrical and magnetic components of the unique polarization signal, as described herein.
  • the signals may correlate with the aggregate conformation state of molecules in the skin structure. By comparing this signal to a standard calibration signal, aspects of the underlying skin structures may be determined.
  • the standard calibration signal may be provided by a catalog of skin structures/ molecules and their specific wavelength of observation. The catalog may be developed by the technique described herein or any other spectroscopic technique.
  • an algorithm 150 may determine a ratio of the reflected polarized light and reflected diffusion light and correlate the ratio with a moisture level. Ideally, close to 100% polarized light may be generated from reflections, however if a portion of the reflected or re-emitted light is diffusion light, such as 95% polarized, 5% diffusion, the amount of diffused light may be correlated with a level of moisture.
  • Incident unpolarized light may interact with a skin structure and lead to varying amounts of polarization of the reflected or refracted light.
  • This polarized reflected or refracted light strength may be measured.
  • This polarization may be as much as 100 percent, however, the reflected polarized strength may even be less than 100% in some cases.
  • the incident angle and the imaged material would help determine the maximum strength possible for the polarization of the reflected or re-emitted light. It should be understood that there may be a maximum amount of polarization with a maximum of 100% for a particular incident angle, but any amount of polarization ranging from 0 to 100% polarized may be expected from the light reflected by any skin structure.
  • an algorithm 150 may determine the concentration of elastin per area of concern.
  • an algorithm 150 may combine moisture levels and skin color into a single, objective assessment. Objective measures may be correlated with an expert grading scale or other external measure.
  • an algorithm 150 may combine an assessment of collagen and elastin concentrations in an area of concern along with the activity of sebaceous glands (as measured by number of glands, percent open/closed, level of clog/ fill). The algorithm 150 may be able to overlay varying wavelengths and intensities and spectroscopic techniques, such as reflectance, excitation/emission, and the like.
  • the algorithm 150 may be able to process and analyze 154 images collected by the device 108 or any other imaging device using unpolarized light, polarized light, or a combination thereof.
  • the algorithm 150 may be able to process and analyze 154 many different types of images, such as thermoelectromagnetic (TEM) images or electromagnetic (EM) images, images collected with incident polarized light, traditional dermoscopy images, spectroscopically resolved images, conventional images, harmonized light images, and the like.
  • the algorithm 150 may be able to calculate a variance measurement of skin state 158 over time.
  • Determining a skin state 158 may also include, in addition to the processing and analysis of images of the skin for various measures and endpoints as described herein, a visual analysis of the images, user entered information, and third party information, such as lifestyle, smoking history, exercise habits, diet, allergies, and the like. For example, a user may enter anecdotal information, such as medication they may be taking, recent overexposure to sun, stage in a menstrual cycle, and the like.
  • an algorithm 150 may comprise spectral convolution of digital images taken with: 1 ) "angled white light", or white light incident on an angle sufficient to produce a polarized reflection; and 2) "non-angled white light", or white light incident on an angle that produces substantially no polarized reflections. While the foregoing discussion will focus on skin as the primary specimen, it should be understood that any specimen, such as material characterized by covalence effects, ionic effects, and hydrogen bond effects, including skin, hair, biological materials, foodstuffs, liquid, wine, metallic materials, non-metallic materials, and the like may be specimens for the algorithm 150.
  • a digital image of a specimen is captured with non-angled light 3502 and angled light 3504, blue and red color channel histograms are generated for each image 3508, 3510 and are normalized to the relative intensity of the light, and the color channel histograms are correlated to a wavelength scale 3512, 2514.
  • the spectral convolution proceeds in two steps. The first step involves subtracting, for each of the red and blue color channels, the color channel histogram for angled light from the color channel histogram for non-angled light 3518. Two composite histograms are generated, the blue color channel composite histogram and the red color channel composite histogram. The second step of the spectral convolution involves subtracting the blue channel composite histogram from the red channel composite histogram 3520.
  • a specimen 3604 which may be any suitable material for imaging as described previously, may be illuminated with non-angled white light 3608 and angled white light 3610.
  • varying the angle of incidence affects the depth of penetration of the light to various skin structures.
  • For each skin structure which may correspond to a particular known depth within the skin, there may be an angle of incidence which produces a polarized reflection.
  • polarized 3614 and/or diffusion 3612 captured by an imaging device 3602
  • information on the underlying skin structures responsible for the reflection may be obtained.
  • angled white light refers to incident white light that is directed towards the specimen at an angle sufficient to produce a polarized reflection.
  • non-angled white light refers to incident white light that is not directed at a specific angle towards the specimen and is diffuse.
  • the non-angled white light may produce reflected white light, polarized light, or a combination thereof.
  • reflected polarized light generated by non-angled white light may be of a different characteristic than polarized light generated by angled white light.
  • Maxwell's color triangle in Fig. 37B, may facilitate an understanding of the nature of white light.
  • Maxwell's color triangle depicts the complete visible color spectrum, with reference to specific wavelengths.
  • a simplified version is used with straight lines, shown in Fig. 37A.
  • Each of the vertices of the outer triangle corresponds to an ideal color, either ideal green, red, or blue going clockwise from the top.
  • a Maxwell triangle mixing of two of the three color components occurs with every possible proportion. As one travels from the side towards the center, the third primary color becomes increasingly important.
  • the coordinate system may be validated, as represented by the internal triangle 3708.
  • the internal triangle 3708 validates the system when the sides are parallel to the limits of the color space lines of the original coordinate system. If they are not parallel, then the coordinate system is not valid.
  • an RGB histogram for each color channel is generated for each of the images.
  • An RGB digital image has three color channels: red, green, and blue. Each of these channels may be examined and analyzed separately.
  • a blue color channel histogram is generated for the image taken with non-angled white light and another blue color channel histogram is generated for the image taken with angled white light.
  • a red color channel histogram is generated for the image taken with non-angled white light and another red color channel histogram is generated for the image taken with angled white light.
  • an automated system may be used to generate the histograms for each color channel, as shown in Fig. 38.
  • a histogram 3802 may be generated for that channel.
  • the histogram may be normalized to the relative intensity of the light. Normalizing the histograms to the intensity of incident light is important to be able to process the histograms generated from different images.
  • the RGB color channel histograms are then correlated to a specific wavelength scale to generate RGB color channel spectral plots.
  • the data from the pair of images are then combined mathematically in two steps.
  • the blue color channel spectral plot generated from the image taken with angled white light 4004 is subtracted from the blue color channel spectral plot generated from the image taken with non-angled white light 4002 to generate a blue color channel composite spectral plot.
  • the two spectral plots 4002, 4004 are shown first overlaid in Fig. 40A and then subtracted in Fig. 41A.
  • the red color channel spectral plot generated from the image taken with angled white light 4008 is subtracted from the red color channel spectral plot generated from the image taken with non-angled white light 4010 to generate a red color channel composite spectral plot.
  • the two spectral plots 4008, 4010 are shown first overlaid in Fig. 40B and then subtracted in Fig. 41 B. Subtraction may be facilitated by aligning the spectral plots by wavelength and mathematically subtracted the normalized intensities at each wavelength. For example, if the intensity is 0.005 at 470 nm for the blue channel spectral plot from angled white light and the intensity at the same wavelength of the blue channel spectral plot from non-angled white light is 0.003, the resultant spectral plot would comprise an intensity of -0.002 at 470 nm.
  • the specific intensities and wavelengths in the spectral plots reflect the specific properties of the underlying material and the angle at which the material was exposed to light.
  • Fig. 42 the two color channel composite, normalized spectral plots are then combined to create a unique spectral signature of the specimen.
  • the normalized, composite blue channel spectral plot is subtracted from the normalized, composite red channel spectral plot.
  • the scale is determined as a difference in wavelengths between the red and blue color images, starting from the darkest point in both colors. This scale is based on the mathematical coordinate system for Maxwell's color triangle. For example, and referring to Fig. 43, the lower part of Maxwell's color triangle is shown plotted out in Fig. 43B, with arrows indicating the correspondence in the plot with the position on the color triangle shown in Fig. 43A.
  • Position 1 in the plot corresponds to ideal blue in Maxwell's color triangle
  • position 2 corresponds to true white
  • position 3 corresponds to ideal red.
  • Points 1 and 3 are aligned when convoluting the composite spectral plots to obtain the spectral signature, hence the unit scale on the convoluted histogram is a difference of wavelength (e.g. 500-400nm to 700-400nm).
  • the spectral signature obtained may be analyzed for a number of characteristics, such as number of peaks and troughs, amplitude and shape of peaks and intermediate structures and patterns, and the like.
  • Various mathematical, visual, and algorithm processing techniques may be used to process and analyze the spectral signatures.
  • the spectral signatures obtained for various specimens may be unique, for example, the spectral signature in Fig. 44A is for light skin while the spectral signature in Fig. 44B is for dark skin.
  • the algorithm may be used for identifying metal composition, purity, strength, and the like.
  • the spectral signature may be used to distinguish between metals.
  • the spectral signature in Fig. 45A is for a pure metal, aluminum, while the spectral signature in Fig. 45B is for an alloy of metals, PbMnTe.
  • the spectral signature may also be used to distinguish between similar substances with different compositions.
  • the spectral signatures in Fig. 45B and Fig. 45C are both for the PbMnTe alloy but the alloy of Fig, 45B is of a different composition as compared to the one in Fig. 45A.
  • the algorithm 150 may be used to analyze water quality, composition, purity, and the like.
  • the spectral signature for filtered water is shown in Fig. 46A in comparison with the spectral signature for highly purified water, shown in Fig. 46B.
  • the spectral signature may further be enhanced by subtracting the spectral contribution attributable to the source light from the reflected light spectrum in order to normalize the spectral signature to specific skin conditions.
  • the spectral signatures in Figures 51 through 54 may be normalized by subtracting the source spectral signature from the reflected light spectral signature.
  • the resulting spectral waveform is normalized to only the changes in the skin from the interaction with incident light. In this way, specific type of incident light may be used which may be more amenable to detecting certain structures, compositions, or conditions.
  • a spectral signature for the subtraction of RGB histograms for angled light from non- angled light may be calculated and used to subtract from the final spectral signature for the material.
  • positive intensities 5101 represent a net reflection or emission at specific wavelengths based on material characteristics while negative intensities 5102 represent a net absorption from the source light's spectral signature. Negative intensity 5102 indicates no absorption of source light at specific wavelengths based on material characteristics.
  • the source may be selected for use in examining specific biophysical or material criteria in order to produce a specific waveform for analysis.
  • Figure 52 it is possible to determine changes in skin state 158 using spectral characteristics of specifically selected light sources based on specific biophysical criteria.
  • Figure 52 shows a comparison of PB(S-O) signatures showing an example for differences between benign/healthy expected tissues and diseased tissue. Changes, such as in the 462nm-485nm range in Fig. 52, such as absorption or emission within the spectral diagram may correspond to additional changes in tissue processes, tissue activity, or presence of other molecules that indicate a changed state of skin. By measuring these changes, it is possible to determine healthy and diseased or disturbed states of the skin. The characterization of healthy tissue based on emission and or absorption may be determined at a specific reference wavelength 5209 that is based on the source light selection.
  • the spectral signature of healthy skin 5201 using a specific source light shows little or no absorption or emission in the spectral range 5205.
  • the spectral diagram shows normal spectral characteristics 5206 right of the reference wavelength at line 5203. Additionally, characteristics in the area 5207 to the left of the reference wavelength at the line 5204 indicate diseased characteristics due to re-emission or emission 521 1 , while the area 5208 to the right of the line 5204 indicates absorption 5210.
  • the area 5207 corresponding to wavelengths 462nm-485nm shows additional activity due to additional changes in tissue processes, activity, or presence of other molecules that indicated a changed state of skin.
  • the size and shape of peaks, troughs, curves, frequency, spacing, specific sections of wavelength differences, and the like may also correspond to concentrations of molecules, stages of disease progression, skin characteristics, and the like.
  • the algorithm 150 may only use reflected polarized light due to increased selectivity for specific biophysical or material characteristics.
  • the reflected polarized and/or emitted polarized light spectral signature 5302 may be much more sensitive to certain biophysical characteristics than simple white light convolution 5301.
  • Figure 53 depicts the spectral signatures for malignant melanocytic lesions.
  • the spectral diagram showing emission 5305 in the polarized 5302 spectral signature is much taller than the spectral diagram showing emission 5303 in the nonpolarized 5301 spectral signature.
  • the spectral diagram showing absorption 5306 in the polarized 5302 spectral signature is much deeper than the spectral diagram showing emission 5304 in the nonpolarized 5301 spectral signature.
  • the algorithm 150 may be used to analyze healthy and non-healthy or malignant skin.
  • the spectral signatures for healthy, non-pigmented skin 5401 and 5402, healthy pigmented skin 5403 and 5404, and malignant pigmented skin 5405 and 5406 are shown in Fig. 54. Both polarized (bottom) and white light (top) spectral signature convolutions are shown for purposes of comparison.
  • the spectral signature of normal, healthy skin 5401 and 5402 shows very little absorption or emission relative to the source light spectrum around referent wavelength 485nm.
  • the healthy, benign pigmented skin lesion 5403 and 5404 shows very little absorption or emission to the left or right of the reference wavelength 485nm.
  • the malignant tissue clearly shows absorption and emission effects around the referent wavelengths with higher amplitudes and shifting of the spectral diagram peaks and valleys.
  • these spectroscopic techniques may be useful for a variety of analytical tests where the test substrate comprises a light-sensitive component.
  • elements of the waveform may be tagged and tracked over time in order to track changes in the characteristics of the material or specimen, such as peaks, troughs, curves, frequency, spacing, specific sections of wavelength differences, and the like.
  • the algorithm 150 may be incorporated for automated measurement as part of an integrated device that conducts surface analysis, such as a skin imaging device or metal testing device.
  • the algorithm 150 may be part of a remote analysis system whereby a surface imaging device may capture images and send them to a processing center where the algorithmic computations may be made.
  • the algorithm 150 may be used for the analysis of hair in order to determine the health of hair follicles, composition, and the like.
  • the algorithm 150 may be used for the counterfeit analysis of money. For example, a unique signature may be created for each series of appointment and/or issue.
  • the algorithm 150 may be useful for the analysis of anti-perspirant effectiveness.
  • axillary odor may be an indication of sickness or some other medical condition, such as lymphoma, apocrine gland sweating, hyperhidrosis, hidradenitis suppurativa, or other sweat related medical problems.
  • the algorithm 150 may be useful in determining a scale of deodorant effectiveness based on an individual's specific sweat gland activity and type.
  • the algorithm 150 may enable measuring the activity of sweat glands located in the axilla, feet, palms, and the like.
  • the algorithmic analysis may enable the classification of sweat glands and may enable the suggestion of appropriate products/ingredients for treatment.
  • the algorithm 150 may be able to determine the effectiveness of an anti-perspirant based on the impact on sweat gland activity.
  • the algorithm 150 may be useful for determining a veterinary condition, such as Mad Cow disease.
  • a veterinary condition such as Mad Cow disease.
  • imaging the tongue of a cow or any mucosal or dermal area where the disease may manifest may allow for the detection of a disease state using the algorithm 150.
  • White light imaging, as described herein, in combination with UV imaging may facilitate detection of a Mad Cow disease state.
  • the algorithm 150 may be useful for monitoring post-operative cosmetic concerns, such as stretch mark progression and diminishment, and the like.
  • the algorithm 150 may be useful for predicting and monitoring secretion from the mammary glands of lactating women. If milk production is predicted to be low based on the algorithmic analysis, suggestions may be made to increase milk production.
  • an algorithm 150 for determining a skin state 158 may facilitate measuring, tracking, and monitoring a skin state 158 as well as the effectiveness of a regimen 1 18, topical and/or systemic therapies, avoidance routines, diet, and the like.
  • the skin state 158 may be measured at intervals and current measurements may be compared to previous measurements to determine skin health changes.
  • the results from the algorithm 150 may feed into a recommendation engine to provide feedback and modifications to aspects of the regimen 118.
  • an algorithm 150 for determining a skin state 158 may enable a diagnosis.
  • the diagnosis may be an early diagnosis by distinguishing between critical and non-critical indications.
  • the algorithm 150 may be able to distinguish between a minor sunburn and a third degree sunburn requiring medical attention.
  • Use of the device 108 to capture images enables a user to readily transmit the images to any practitioner for remote assessment, to track progression of a skin condition, rapidly compare images to previous images, other user images or third party images, such as images in a dermascopic database 1 15, and the like, and to make an immediate assessment with no need for historical knowledge, and the like.
  • Historical data and the results of modeling tools 132 may be compared to the images to assist in analysis, either by an algorithm 150, a practitioner, or a practitioner employing an algorithm.
  • user input in the form of audio, video, or text anecdotes describing the issue, such as a level of pain, a sensation of heat, an itchiness, and the like, may be useful in analyzing the images to determine a diagnosis.
  • the algorithm 150 may enable non-linear regression, such as principal component analysis (PCA), which may be a biomedical analysis used in conjunction with spectrometric analysis for analyzing medical and health conditions.
  • PCA principal component analysis
  • the algorithm 150 may enable a simple pattern analysis for diagnosis.
  • the algorithm 150 may be able to determine the thermo- and electroconductivity conditions of skin lesions.
  • the algorithm 150 may be able to diagnose a melanocytic lesion by examining the images for the relationship of changes in collagen and porphyrin, as a change in collagen but not porphyrin may indicate a change from a normal lesion to a dysplastic lesion.
  • the skin state 158 may be compared with a table of indicators for various types of lesions.
  • the algorithm 150 may be able to diagnose UV damage. UV damage may be difficult to assess from a conventional superficial view as UV damage may be present even in wrinkle-free skin.
  • UV damage may be assessed by examining skin structures for an increase in melanin production; global distribution, damage and count of superficial blood vessels; change in hemoglobin count: changes in the thickness of the epidermis; changes in the quantity and global distribution of collagen, and the like.
  • diagnosis may not require processing the border of the lesion, as it may not be a key factor in final analysis of the skin lesion.
  • the algorithm 150 may be able to diagnose oral cancer.
  • an algorithm 150 for determining a skin state 158 may enable cosmetics manufacturing validation or cutaneous clinical trials.
  • a skin state 158 may be determined prior to medical, non-medical, skin care product or cosmetics application and a time lapse series of images may be acquired to track the medical, non-medical, skin care product, and cosmetics effectiveness.
  • the skin state 158 may be stored in the device 108 itself, on a PC, in a central server, a salon record, an e-medicine record, a medical repository, a cosmetic clinical studies database 1 15, a mobile device, and the like.
  • the device 108 may communicate with a user interface 102, an online platform 120, a mobile platform 124, and the like to upload, deliver, share, and/or port images, analysis 154, skin states 158, data, track history, user profiles, and the like, as will be further described herein.
  • a user may use a device 108 embodied in a mobile device to capture an image of the skin and upload it to a mobile platform 124 for analysis 154 to determine a skin state 158.
  • the user may receive a personalized regimen 1 18 for sun protection given the user's skin state 158.
  • Other factors that may be used to determine the regimen 1 18 may be the current UV Index, time of day, location, kind of sun protection product the user prefers, and the like.
  • the user may have already obtained a skin state 158 determination and they need not upload a new image but simply request a regimen 1 18 recommendation from the mobile platform 124 given the already determined and stored skin state 158.
  • an algorithm 150 for determining a skin state 158 may enable an analysis of differences and similarities among peers.
  • the algorithm 150 may determine peers of a user who may be most like them in terms of skin state 158 or other criteria such as gender, age, ethnicity, behaviors such as smoking, working outdoors, and the like, diet, regimen 1 18, and any other identifying factors.
  • the algorithm 150 may be able to interface with an online platform 120, third party database 1 15, or third party service provider 1 1 1 1 to access skin states 158 and demographic information for comparison.
  • a user may wish to know what other women in their mid-30's of the same skin color are using for foundation.
  • the algorithm 150 may enable grading of the skin relative to a peer group.
  • a user's skin state 158 may be compared to a previously defined skin state 158 in order to monitor the skin state 158 over time.
  • a user's skin state 158 may also be compared to the skin state 158 of other individuals or groups of individuals to identify peers whose skin state 158 is closest to the user.
  • the system may display the skin care products and/or skin care regimen that is effective for the peer.
  • any comparison among users may be made by the system, such as a comparison of at least one of age, gender, location, climate, skin color, ethnicity, and the like, to identify a peer.
  • the device 108 captures data from users and determines skin states 158, the information may be fed back into the algorithm 150 to further enhance the peer identification and product recommendation process.
  • an algorithm 150 for determining a skin state 158 may enable prediction/simulation tools 132. Having determined a skin state 158, an algorithm 150 may be able to simulate progression of aging, simulate skin care treatment effects and skin care and cosmetic regimens 118, simulate progression of a skin condition, and the like. Referring to Fig. 6, a user may use a user interface 102 to access the simulation tools 132. In the example, the image of an entire face may be used but it should be understood that simulation tools 132 may be used to generate simulations for any size area of concern. After selecting or capturing a starting image, a user may indicate the kind of simulation they would like to perform.
  • the user may like to perform a simulation of aging only, or a simulation of aging and treatment effects.
  • the simulation tool 132 may return data on overall appearance, wrinkle count, elasticity, luminosity, moisture, product usage simulation, and the like.
  • the output may also include a split image with the original face on one half and a new simulated output on the other half.
  • an algorithm 150 for determining a skin state 158 may enable skin cycle monitoring 140.
  • skin conditions with a cyclical nature may be monitored, predicted, pre-empted and the like.
  • skin conditions associated with a season, weather, pollen count, hormone level, environmental condition and the like may be identified and monitored by a skin cycle monitor 140.
  • an algorithm 150 may be used to generate searchable and/or indexable tags to associate with images and may take advantage of image tagging. Images may be tagged with information relating to the content of the image, such as information relating to a skin state, a skin condition, a gender, an ethnicity, an age, a regimen, a treatment, and the like. The information may be gathered by algorithmic analysis, user input, visual inspection of the image, and the like. An algorithm 150 may be used to perform a search 103 using the information associated with the image as a search term. In embodiments, the information may be stored separately from the image, such as an entry in a user profile, or may be stored in association with an image.
  • a search 103 may be performed against information or images from other users' or a third party database 1 15 to identify similarities or differences in images or information. For example, a user may use information to search for peers with a similar skin condition in order to determine what to expect as the condition progresses.
  • the search 103 or query for advice or recommendation from experts may be performed against product information 190, wellness information 192, skin care regimens 1 18, third party experts 105, and the like.
  • a user may use information to search for product information 190 indicating an effectiveness of a product for the user's skin condition.
  • the search 103 may be performed to determine an availability of a product, an inventory of a product, a price of a product, and the like.
  • a user may use the information to search a store catalog for a specific product that may be effective for the user.
  • the user may be pale skinned and be interested in identifying an inventory of a self-tanning product formulated specifically for pale skin.
  • the image itself may be used as a search query 103.
  • the image itself may be used to search a database 115 of skin images.
  • images and information entered into the system 104 may be leveraged to develop new algorithms 150 for enhanced diagnosis.
  • algorithms 150 may be developed for non-skin specific diseases with dermal manifestations, such as rheumatoid arthritis.
  • an algorithm 150 may be useful for analyzing product characteristics.
  • an algorithm 150 may be able to take product ingredients and match the product up with a projected effectiveness on a particular skin state 158.
  • an algorithm 150 may use RGB color analysis.
  • the algorithm may employ standard RGB analysis and correlation with skin structures in determining skin phototype.
  • the calculation of parameters for determining skin phototype is fast and the skin phototype can be found in a very short period of time using a simple skin and cosmetic parameters classification routine.
  • Exemplary embodiments of the present invention are directed to a method and system for determining skin characteristics and cosmetic features.
  • the method and system provide a minimal error and speed efficient skin analysis.
  • the present technique describes a method and a system for determining a skin phototype of acquired digital image in a Red Green Blue (RGB) color system.
  • RGB Red Green Blue
  • a method for determining skin characteristics and cosmetic features using color analysis includes a step of analyzing the color of skin images in a pixel by pixel manner in a Red Green Blue (RGB) color system for an acquired digital image.
  • the colors obtained in a device dependent RGB color system are then converted into device independent standard RGB color system (sRGB) which will be used in subsequent color analysis.
  • the step of analyzing the color of skin images in a pixel by pixel manner in a sRGB color system for an acquired digital image comprises analyzing a picture of a part of a person's skin by generating a table of most frequent colors appearing in the picture.
  • the sRGB color system has been used for image analysis. Determination of other skin characteristics (e.g. elasticity, melanin, oil concentration etc.), melanoma, skin related tumors and skin related disorders may require image analysis based on various color systems such as YIQ, YCbCr, L * a * b * , L * uV and HSL/HSV.
  • the enhancement of the current algorithm 150 may include at least one of these color systems and its/their correlation with presented sRGB analysis. This will most likely lead to in-depth refinement and overall accuracy of the current results as well as further embodiments of the present invention. Apart from the human skin related issues, this method of image analysis is also applicable to any content whether it be animals, products, plants or any other material whose surface needs to be analyzed by a digital image.
  • a method for determining skin characteristics and cosmetic features using color analysis includes a step of generating a sample of most frequent sRGB colors responsive to analyzing the color of skin images in a pixel by pixel manner in the RGB color system for the acquired digital image after converting colors obtained in a device-dependent RGB color system into a device-independent standard RGB color system (sRGB).
  • the step of generating a sample of most frequent sRGB colors responsive to analyzing the color of skin images in the sRGB color system for the acquired digital image comprises preserving a plurality of sRGB color values.
  • a method for determining skin characteristics and cosmetic features using color analysis includes a step of modeling the standard R, G and B component color distribution with Gaussian probabilistic distribution with estimated parameters (expected value and standard deviation) of the generated sRGB color sample for the acquired digital image further including approximating colors of the generated sRGB color samples by a Gaussian normal distribution.
  • the step of approximating colors of the generated sRGB color samples by a Gaussian normal distribution comprises approximating colors of the generated sRGB color samples by a superposition of a plurality of Gaussian normal distributions.
  • a method for determining skin characteristics and cosmetic features using color analysis includes a step of generating a phototype of the skin through a decision tree unit responsive to the estimated distribution model parameters colors.
  • the phototype of the skin is generated according to a corrected Fitzpatrick classification, or any other applicable color classifier.
  • the step of generating a phototype of the skin according to corrected Fitzpatrick classification includes generating a phototype of the skin according to a skin type scale which ranges from very fair skin to very dark skin.
  • the system for skin phototype determination using photograph analysis includes a subsystem for determination of cosmetic features for a human element and a veterinary element.
  • the cosmetic features further include features pertaining to hair, nail and skin.
  • the image of the skin sample of a person's body can be captured by any digital camera.
  • the acquired digital image sample of the person's skin may be analyzed in a pixel by pixel manner in the RGB color system.
  • a table of most frequent sRGB colors which appear in the image may be generated.
  • the generated table may consist of 256 most frequent colors which appear in the image of the person's skin.
  • the color samples obtained from the image may be approximated by a Gaussian normal distribution (or a (scaled) superposition of few Gaussian normal distributions).
  • the estimates of expected value (using weighted mean) and standard deviation (using unbiased (n-1 ) method as the precise expected value is unknown / estimated) for each of the acquired digital images may be evaluated.
  • the phototype of the skin may be determined through a decision tree with the estimated expected value and standard deviation. Fitzpatrick classification may be used for categorizing a skin phototype in accordance with a skin type scale which ranges from very fair skin to very dark skin.
  • a flowchart 5800 illustrating a process for determining a skin phototype of an acquired digital image of a part of a person's skin is shown.
  • the process starts at block 5810 wherein an image of a part of a person's skin is captured.
  • the image capturing device may be a digital camera or the like.
  • Processing flow continues to logical block 5820 wherein analysis of the acquired digital image is done in a pixel by pixel manner in a RGB color system. After converting all colors from the device-dependent RGB color system into a device-independent standard RGB color system (sRGB), a table of most frequent colors which appear in the acquired digital image may be generated using a quantization technique at block 5830.
  • sRGB device-independent standard RGB color system
  • a plurality of sRGB color values/samples generated between a range of values 0 and 255 may be preserved for further analysis.
  • This range of values has been proven to be more convenient for skin type determination than the one between 0 and 1 .
  • the transformation from one to another can be done simply by dividing the values with 255 and vice versa.
  • approximations of colors on the samples are done by Gaussian normal distribution, at block 5860 the estimates expected value and standard deviation are evaluated.
  • the photoype of skin of the acquired digital image is determined according to the corrected Fitzpatrick classification using a decision tree.
  • the decision tree may be an algorithm wherein the estimated expected value and standard deviation are equated to the values of Fitzpatrick classification/notation values in determining the phototype of the skin.
  • the effectiveness of this approach may be seen in research regarding parametric skin distribution modeling for skin segmentation / detection.
  • a diagram depicting a pixel view of an acquired digital image of a sample of person's skin is shown.
  • the image of a sample of a person's skin is captured under white emitting light.
  • the image may be captured by any digital camera and the like under white emitting light.
  • An analyzer coupled to the image capturing device may analyze the acquired digital image in a pixel by pixel manner in the RGB color system.
  • the analysis of the acquired digital image in a pixel by pixel manner in the sRGB (after RGB to sRGB color system conversion) is not only limited for determining skin phototype but also may be useful for other purposes like classification of other skin characteristics (e.g. elasticity, melanin, oil concentration etc.), melanomas and other skin tumors/disorders and the like.
  • Fig. 60 a diagram depicting a pixel view of the acquired digital image of a part of person's skin after quantization is shown.
  • the image of the sample of the person's skin is captured under the white emitting light.
  • the image may be captured by any digital camera and the like under white emitting light.
  • the analyzer coupled to the image capturing device analyzes the acquired digital image in a pixel by pixel manner in the RGB color system.
  • the analysis of acquired digital image in a pixel by pixel manner in the sRGB (after RGB to sRGB color system conversion) is not only limited for determining skin phototype but also may be useful for other purposes like classification of other skin characteristics (e.g.
  • Color quantization or color image quantization is a process that reduces the number of distinct colors used in an image, usually with the intention that the new image should be as visually similar as possible to the original image. Color quantization is critical for displaying images with many colors on devices that can only display a limited number of colors, usually due to memory limitations, and enables efficient compression of certain types of images.
  • An image quantization technique may be applied to the captured image.
  • a table of 256 most frequent colors which appear on the acquired digital image of the part of person's skin may be generated using a sampling device coupled to the analyzer.
  • the acquired color samples from a digital image may be preserved in the sRGB color system.
  • the generated color samples may be preserved in their range of values between 0 and 255 in the sRGB color system. This range of values has been proven to be more convenient for skin type determination than the interval ranging between 0 and 1 .
  • colors of the samples may be approximated by a Gaussian normal distribution (or a (scaled) superposition of few Gaussian normal distributions) through an approximating device coupled to the sampling device. Further the estimates of expected value (using weighted mean) and standard deviation (using unbiased (n-1 ) method as the precise expected value is unknown / estimated ) for each of the acquired digital image may be calculated with the approximating device coupled to the sampling device.
  • FIG. 61 a diagram depicting a Histogram / Distribution of standard R, G and B colors of one of the taken photographs of a patient whose skin phototype is classified as type III by Fitzpatrick, and their Gaussian normal approximation / hull is shown.
  • the estimates are compared with the decision tree described below for determining skin phototype.
  • the phototype of skin is determined according to corrected Fitzpatrick classification.
  • the Fitzpatrick Skin Typing Test questionnaire (skin type scale) which ranges from very fair (skin type I) to very dark (skin type VI) is often used to determine skin phototype.
  • Dermatologists use the Fitzpatrick Classification Scale to classify a person's complexion and tolerance to sunlight.
  • the Fitzpatrick scale classifies skin types from I to VI.
  • Type I Very white or freckled skin, always burns with sun exposure (very fair; often in people with red or blond hair and blue eyes)
  • Type II - White skin usually burns with sun exposure (fair; often in people with red or blond hair and blue, green, or hazel eyes)
  • Type III White or olive skin tone, sometime burns with sun exposure (fair; seen in people with any hair or eye color)
  • Type IV - Brown skin rarely burns with sun exposure (common in people of Mediterranean descent)
  • Type V Dark brown skin, very rarely burns with sun exposure (common in people of Middle- Eastern descent)
  • the images of skin are captured under white emitting light with an image capturing device, such as a digital camera, video camera or the like.
  • An analyzer analyzes the captured image pixel by pixel of a part/sample of a person's skin.
  • a sampling device coupled to the analyzer generates a table of 256 most frequently occurring colors in the captured image.
  • the acquired color samples from the digital image are preserved in the sRGB color system.
  • the generated color samples are preserved in their range of values between 0 and 255 in the sRGB color system.
  • An approximating device coupled to the sampling device may calculate the estimates of expected value (using weighted mean) and standard deviation (using unbiased (n-1 ) method as the precise expected value is unknown / estimated) for each of the acquired digital images.
  • a decision tree coupled to the approximating device determines the skin phototype. From this imaging, it turns out that expected values of R and B may be sufficient for determining skin phototype according to the following decision tree.
  • Fig. 62 is a diagram depicting a Histogram / Distribution of R, G and B colors of one of the patient's photographs whose skin phototype is classified as type VI by Fitzpatrick, and their Gaussian normal approximation / hull.
  • the estimates are compared with the decision tree mentioned above for determining the phototype of the skin.
  • FIG. 63 a flowchart 6300 illustrating an algorithm 150 for determining the skin phototype according to the estimated values of mathematical expectation for standard R and B color in sRGB color system is shown.
  • the flow chart describes the algorithm 150 developed in accordance with the present technique wherein the photograph of a part of person's skin is captured with a digital camera or the like under white emitting light at logical block 6310.
  • the captured digital image is analyzed in a pixel by pixel manner in the RGB color system.
  • a quantization technique is employed for analyzing the captured image in a pixel by pixel manner in the sRGB color system at logical block 6330.
  • the color samples obtained from the image can be approximated by a Gaussian normal distribution (or a (scaled) superposition of few Gaussian normal distributions). Therefore the estimates of expected value (using weighted mean) and standard deviation unbiased (n-1 ) method (as the precise expected value is unknown / estimated)for each of the acquired digital images may be evaluated.
  • the phototype of the skin is determined according to the decision tree.
  • the various implementations of the present technique provide a variety of advantages. Firstly, the present technique determines skin phototype using regular low-cost digital photography equipment under standard environmental conditions. Secondly, the analysis performed on the captured digital image may be useful in recommendation of cosmetic product and medical or surgical purposes. Thirdly, the picture quantization algorithm and calculation of estimates expected value and standard deviation are fast, this makes it easier to determine skin phototype in a short span of time using a simple routine. Fourthly, the analysis performed may be useful for classification of other skin characteristics (e.g. elasticity, melanin, oil concentration etc.), melanomas, skin tumors or disorders and the like.
  • other skin characteristics e.g. elasticity, melanin, oil concentration etc.
  • new algorithm 150 development by practitioners, users, service providers 1 1 1 , and the like may be enabled by a software development kit that anyone could use to develop new algorithms 150 and APIs 154 for the device 108.
  • a process for collecting images, performing skin analysis, communicating findings and scheduling follow up may commence with image capture by a user using a device 108.
  • the user may also answer questions or provide additional details regarding a user-entered imaging, cosmetic regimen, area of concern, or the like.
  • the data may be communicated to an analyst 304 or a computer for analysis 154 by any communication method, such as over a network, the Internet, wirelessly, and the like.
  • a payment system 302 may be accessed by the user.
  • an insurance company may access the data, however, payment may be effected or requested by any interested entity such as a one-time payment by the user, a subscription by the user, a third party service provider 1 1 1 , a platform 120,124, a practitioner, and the like.
  • the entered data may be analyzed by the analyst, by software in real-time, by analysts assisted by software assistance, and the like.
  • An initial analysis may be to determine data integrity. In instances where the data do not pass the integrity test, it may be communicated back to the user.
  • the analyst's assessment may be assisted by software that uses an algorithm to determine type of condition and/or recommended care/treatment. Historical analysis and data, and modeling tools may be used to assist the analyst's assessment.
  • the analysis 154 may be stored 308 by the system and/or submitted to a practitioner for approval 310. In embodiments, storage 308 may require practitioner approval 310.
  • a test of the severity 312 may determine the selection of an appropriate method of communication with the user. If the result of the test 312 is positive, the user may be notified immediately by a preferred communication method, such as telephone, instant message, and the like. If the result of the test 312 is negative, the user may similarly be notified, however, the notification may take a less urgent route, such as by email or postal mail.
  • the software tool may recommend an appropriate communication method and media, based on the assessment and may populate preset templates with the information/message to be communicated.
  • notification by any means may also include a notification of practitioner availability.
  • the analysis 154 may trigger a practitioner availability / scheduling tool. For example, prior to transmitting the results on severity 312 to the user, a practitioner availability may be assessed and transmitted simultaneously. The user may access availability and scheduling tools in order to obtain and confirm an appointment time.
  • a user interface 102 for a skin analysis system 104 may be used to interface with the device 108, store images, deploy algorithms 150, track a skin state 158 by keeping track of images from any number of areas of concern, the interval between image capture, a projected next image capture date, communicate findings to a practitioner, interact with simulation tools 132, skin type determination tools 130, a skin cycle monitor 140, practitioner availability / scheduling tools, and the like.
  • the user interface 102 may be operable as an application running on a device 108, a computer, server, kiosk, or the like, on an online platform 120, on a mobile platform 124, and the like. Any and all aspects of the user interface 102 described herein may be applicable to the user interface 102 running in any environment.
  • the user interface 102 for the device may be integral with the device 108, such as embodied in the keypad of a communications device or a series of buttons, switches, keys and the like disposed on the device 108, or may be external to the device 108, such as software running on a computer, on the Internet, on an intranet, on a mobile communications device, on an online platform 102, on a mobile platform 124, and the like.
  • the user interface 102 may be used to modify a setting of the device 108, such as the magnification, light source, light intensity, wavelength of light, angle of light, electrical and magnetic properties of the light, positioning of sensor, duration of image capture, image size, data storage, data transmittal, and the like.
  • a setting of the device 108 such as the magnification, light source, light intensity, wavelength of light, angle of light, electrical and magnetic properties of the light, positioning of sensor, duration of image capture, image size, data storage, data transmittal, and the like.
  • the user interface 102 may organize and index images captured by date, area of concern, skin state, and the like. For example and without limitation, as seen in the Fig. 5, four images captured from the same area of concern are indexed by their number within the series.
  • the user interface 102 may show in real time the field of view on the skin being imaged as well as populate the user interface 102 with the images once taken or once submitted by the user.
  • the user interface 102 may keep track of the first image, latest image, next image, and the like.
  • the user interface 102 may allow users to shuffle through image s and use the images as a basis for simulation 132, as described herein.
  • the user interface 102 may be used to set a reminder for next image capture.
  • the user interface 102 may be used to create a report of the images and skin state 158.
  • the user interface 102 may be used to transmit the report to a practitioner.
  • the user interface 102 may be used to launch a skin type test.
  • the user interface 102 may depict a form of a body. As a user interacts with the depiction of the body, such as with an indicating device, the portions of the body that have been imaged may be linked with the images such that the images may popup or be otherwise accessed.
  • the user interface 102 may be adapted to collect data from the user in response to prompts.
  • the user interface 102 may employ an algorithm 150 to check the integrity of the captured images.
  • the user interface 102 may guide the user in capturing images and providing user input in association with the images.
  • the user interface 102 may interface with host hardware 108 or third party hardware 109.
  • Hardware 108, 109 may comprise an imaging device that may connect with a computer, online platform 120, mobile platform 124, and the like via the user interface 102 and enable users to capture an image that enables measure various skin health, condition and type parameters.
  • the hardware device 108,109 may be a standalone device or connect via or be embodied in a computing device of either medical or non-medical use.
  • the user interface 102 may guide the connection process for the hardware device 108, 109.
  • the device 108, 109 may store images, reports and recommendations generated and maintain a repository of the image, all as part of a skin health record 121 .
  • Third party hardware 109 may comprise devices such as moisture sensors, cosmetic analysis machines, dermascopes, cameras, x-ray machines, MRIs, medical record providers and software, web cameras, communication devices, and the like. Third party hardware 109 may connect to the system 104 seamlessly to enable the user to gain a better analysis, and share such sets of data with other experts or users.
  • the user interface 102 may enable type determination 130.
  • Characteristics may be captured to determine the skin characteristics and the skin state 158 of the users' skin. Broad genetic parameters, such as ethnicity, skin color, location factors, environmental factors (such as pollen count, weather, etc.) , and lifestyle factors may be collected in addition to image and skin health data to determine the users' skin state 158. This skin state 158 may be correlated with product experience ranking and ratings 138 to enable providing a recommendation for most effective products.
  • the user interface 102 may display a regimen 1 18.
  • the regimen 1 18 may be a feature that enables users to learn what products and product usage pattern would work best for their skin based on a hardware- or community-led personalized skin care assessment 160 and / or type determination 130 and product experience sharing via ranking and rating 138 and / or comments regarding product effectiveness and experience (such as smell, taste, feel, texture, color, and the like).
  • the regimen 118 may be a dynamic recommendation based on users' collective inputs as well as experts' inputs on products that would best suit the user's individual needs.
  • the user interface 102 may enable simulation tools 132.
  • Users may be able to upload an image and model various skin parameters (such as moisture level in skin, collagen level, age, and the like.) and observe changes in the image. Additionally, users may be able to model the impact of various products and regimens 118 (skin care, cosmetic, medical, nail care, hair care, and the like) on the image.
  • Simulation tools 132 may enable users to view changes on the entire image or split half of the image to show a comparison of modeled change with current image. The user's images could also be automatically or manually optimized for the best look and the products or regimen 1 18 to obtain that look may be provided.
  • Simulation tools 132 may also enable consumers to model the skin characteristics or state 158 of other selected users or non-users, such as celebrities, luminaries, average users, and the like.
  • the user interface 102 may enable a daily report 134.
  • the daily report 134 may be a report that provides the user information largely customized and most relevant to the user based on their skin state 158.
  • the daily report 134 may list skin care regimen 1 18 to be followed based on the environmental and lifestyle factors relevant to the user, may indicate new product information 190, show the current skin care shelf 114 and rankings 138 or change in rankings 138, feedback from users or experts 105 on products most relevant to the user, and the like.
  • the daily report 134 may include information about clinical trials and upcoming results, new product releases and status, events, various factors affecting the skin such as the day's weather forecast, UV index, temperature, pollen count, and the like, and other data to provide value to the user.
  • the daily report 134 may report on whether a product is nearing its shelf life or may require replenishment based on a recommended usage protocol.
  • the daily report 134 may be provided to the user by the user interface 102, paper, email, SMS, RSS, video or any other communication media.
  • the user interface 102 may enable a wish list 134.
  • the wish list 134 may be a function that a user could select and add products to a part of the skin care shelf 1 14 using drag and drop functionality or other selection mechanism as they surf the web or otherwise access product information 190. They could share this function with other users, friends and/ or family so that other people could see the wish list 134. Other users could then select the products off the wish list 134 and purchase and send the product to the user.
  • the user interface 102 may enable ranking and rating 138.
  • Ranking and rating 138 may be performed for various product characteristics as well as on the various raters and rankers.
  • Product experience may be collected from users in simple ranking and rating 138 format as well as textual comment data to be stored in a database.
  • This ranking and rating 138 may be real time, and may be synthesized to show what is most relevant to the user based on like users or peers, such as users with any of the following characteristics: same age, same sex, same skin type, same ethnicity, geography, moisture levels, and the like.
  • These ranking and ratings 138 may be dynamic ranking and ratings 138.
  • the users may be shown either the total number of rankers / raters and/or the weighted percent score ranking or rating 138.
  • the ranking and rating 138 may comprise any of the following characteristics: perceived effectiveness, smell, touch, feel, texture, ability to absorb product, stains left by product, ease of use, and the like. Users may also be able to upload their images and obtain effectiveness/look ranking and rating 138 for different product recommendations from other users or experts 105. For example and without limitation, a user may upload data and/or images and request rating and feedback on better products from an herbal expert in India, aging expert in Japan, and the like. Users providing ranking and rating 138 for various products may themselves be rated by other users. This may enable selection of the most effective and unbiased users and help identify potential experts 105. A small select group of highly ranked users may be offered exclusive writing / publishing and ranking / rating privileges.
  • the user interface 102 may enable a skin cycle monitor 140.
  • the skin cycle monitor 140 may indicate when the last image was collected and countdown to the next scan based on a time interval, such as the time required to replenish the skin or any other interval. Currently, it is believed that the skin replenishes itself every 28 days.
  • the skin cycle monitor 140 may take into consideration age, environmental changes, and other factors to indicate the upcoming scan schedule.
  • the user interface 102 may enable wellness/ health 142.
  • the user interface 102 may collect lifestyle data and also provide lifestyle (such as sleep, rest, exercise, and the like) and health (such as vitamins, food, products usage, and the like) recommendations based on the users particular skin state 158 and characteristics.
  • the wellness and health module 142 may enable the user to obtain a personalized best fit health and wellness schedule and regimen 1 18.
  • the user interface 102 may enable games 148. Users may be able to play games 148 that may enable users to model various products, try different hairstyles, model different hairstyles and clothes, and the like. Users may interact with other users or the computer to make the product selection a fun process. This process could also be used to collect information on user preferences and looks.
  • the user interface 102 may enable a gift guide 144. Based on the user's skin state 158, personalized gift advice may be provided to others in the user's network.
  • the user interface 102 may be embodied in touch screen user navigation.
  • a touch screen system may be employed to enable the user to obtain a visual look and navigate to various parts of the user interface 102, such as navigate to the simulation tools 132, change picture orientation, drag and drop, and the like. Touch screen navigation may be particularly helpful as the hardware device 108 is connected to a computing platform.
  • the user interface 102 may also enable collecting and coordinating information from other devices 109 and/or assessments, such as a dermascope, blood report, biopsy report, and the like to provide additional information for the skin record 121 .
  • the user interface 102 may enable a purchase/ sample portal.
  • the user interface 102 may include a purchase/sample portal that may enable the user to select products and complete a purchase or request a sample to be delivered to a pre-entered address.
  • the portal may be available in various social networking platforms 188 as well as over various computing platforms, such as an online platform 120, mobile platform 124, computer, laptop, mobile phones, and other mobile devices, medical-use devices, and the like.
  • the user interface 102 may enable scheduling and data sharing functionality.
  • a user may be able to schedule online a meeting with a particular expert or practitioner and, if willing, then share a skin state 158 or specific parts of the skin record 121 and history in part or its entirety with the expert or practitioner. Ranked experts and practitioners, availability, and other criteria to aid the selection and scheduling process may be indicated to the user. Experts may also be able to share particular sets of data amongst themselves, such as among practitioners, physician to another physician, physician to spa, spa to spa, and the like.
  • Other inputs 1 12, such as devices, features and data, may be used to augment the data submitted by the user or as the primary data to obtain a personalized assessment regarding the users' beauty, cosmetic, or medical concerns related to skin, hair, nails, and the like.
  • certain devices may be available commercially off the shelf, purchased, proprietary, and the like.
  • a wearable monitor 182 may be an input 1 12 to the system 104 and user interface 102.
  • Wearable skin health monitors 182 may enable real time tracking of changes in the environment and the skins health. These devices could be worn directly on the body, or integrated into clothing, apparel and / or accessories carried by the user. An example would be a user having a device that monitors the UV level, and provides a warning if the sun protection level accorded by a product used by the user falls below a set target level.
  • These wearable monitors 182 may have independent user interfaces 102 or can be programmed for personalized parameters using other input devices.
  • Wearable monitors 182 may also capture various physical parameters like heart rate, blood pressure, exercise rate, water consumption, fat counter, calorie meter, and the like. The monitors 182 may be able to assess hydration levels.
  • a social network 188 may be an input 1 12 to the system 104 and user interface 102.
  • the beauty social network 188 may be a collection of users interested in knowing and sharing information on beauty or medical concerns in a personal, private, and social interactive setting. The intent may be to create a beauty social network 188 where users invite and link to other users to discuss such concerns; obtain information 190, 192; perform ranking, rating, and review of products, regimens, experts, practitioners, other rankers/raters, and the like; complete purchases; access a wish list 119; access a gift guide 144; play a game 148; review their daily report 134; and the like, all the while sharing experiences with other users in their network.
  • product information 190 may be an input 1 12 to the system 104 and user interface 102.
  • a database of product information 190 may comprise product, name, claims, manufacturer information, ranking and ratings 138, packaging information, images, usage parameters, product development history or forecast, special handling, upcoming changes, safety information, effectiveness information, smell, taste, color, texture, price, geography of manufacturing, brand information, consumer feedback and experiences, and other such parameters that may be obtained and/ or maintained to assist in the selection of the best product suited to the users' individual preferences or conditions to obtain the best beauty or medical outcome for their skin, hair, nails, and the like.
  • Similar information on service oriented products such as massages, facials, hair toning, and the like may also be captured as well as information on procedures such as liposuction, Botox treatments, laser hair removal and other beauty, cosmetic and/ or medical procedures related to helping the user look good, improve or maintain a skin state 158, and the like.
  • Manufacturers may register product information 190, contribute information on procedures, products in the pipeline, products in clinical trials, and the like. Users may rank and rate 138 products.
  • a database update utility may update the database with new product information 190, store inventory, and the like.
  • wellness information 192 may be an input 1 12 to the system 104 and user interface 102.
  • Health and wellness information 192 may be captured, such as the impact of various products, primarily but not limited to non-prescription medications, supplements and other consumables that assist and maintain health and wellness (such as vitamins, protein shakes, supplements, and the like).
  • information on lifestyle recommendations (such as sleep, rest, diet and exercise recommendations for particular age groups/ ethnicities, etc.) may be collected and correlated with user preferences and characteristics to enable and provide a holistic health, wellness, and beauty/ cosmetic optimal personalized solution and service.
  • a plug-in web capture 194 may be an input 1 12 to the system 104 and user interface 102.
  • a software component-plug in for internet web browsers and basket or repository may recognize graphic objects on any browsed web page and allow the user to select, and drag-and-drop the graphic object onto a basket or repository onto a page of the web browser, such as a page comprising the skin care shelf 1 14.
  • the graphic objects would be recognized through a standard reference table that would be accessed remotely or reside on the user's PC as part of the plug-in module 194, or as part of a resident software program on the computing platform.
  • Graphic objects may include images for commercial products, such as skin care products or creams, or other objects that are part of any web e-commerce site.
  • the plug-in 194 may highlight the picture, notifying the user that is it recognized, or provide additional information or reference.
  • the plug-in 194 may also recognize brand names, trade names, generic pharmaceutical names, trademarks, and the like.
  • barcode scan 198 may be an input 112 to the system 104 and user interface 102. Bar code information on various products may be captured to assist tracking, identification, price determination and correlation with other product information 190 for identifying similar substitute products, or other allied product information, usage recommendation, other user experience, pricing and delivery information, amongst other relevant sets of data.
  • the bar code scanner 198 could be part of the hand held user device 108, a standalone system, a manual entry mechanism, and the like.
  • conventional information/ questionnaires 101 may be an input 1 12 to the system 104 and user interface 102.
  • Information 101 on the users and products may be captured via dynamic and static questions.
  • Information such as age, sex, location, personal lifestyle traits, smoking habits, sleep patterns, skin dryness / oiliness and moisture levels, product likes and dislikes, experiences with other products along parameters such as smell, taste, absorption, staining propensity, and the like may be captured in a fun manner using questions and answers, games and other interactive tools interspersed at various points of the users' interaction with the service product, system 104, or user interface 102.
  • Information 101 may be captured directly form the user or via an intermediary, and augmented automatically via computer data population, as an output of an algorithm 150 or by experts based on their assessment.
  • Information 101 may be obtained by quizzes, badge- and widget-based forms, on-the-fly, through adaptive, investigative questioning, and the like.
  • Information 101 may be obtained through questionnaires, such as How often do you go shopping?, When do you shop for cosmetics?, Where do you typically go? Why that spot?, Who do you shop with? Why?, What do you ask your friends when asking for advice?, Where do you go for new products/ information about cosmetics?, When do you have to go to a dept store, vs.
  • third party experts 105 may be an input 1 12 to the system 104 and user interface 102.
  • the system 104 may connect various experts such as practitioners, physicians, medical experts, aestheticians, schedulers, product ingredient experts, cosmetologists, herbal, ayurvedic and homeopathic experts, health and wellness experts, media experts, photograph enhancement experts, and the like with users and one another. Users may be able to direct questions to such experts 105 who may be located at different places geographically over the system to obtain personalized advice.
  • the experts 105 may be provided with users' data and characteristics collected and a record of the experts assessment may be retained in the record 121 .
  • the recommendation provided by the expert may be offered to the user for purchase / sample request, and the like. Experts may also be able to flag certain cases or sets of data for discussion or referrals within the expert community or with users.
  • third party hardware 109 may be an input 1 12 to the system 104 and user interface 102.
  • the system may connect with various third party hardware 109, such as existing imaging solutions, camera devices, computers, lighting systems, sports devices such as pedometers, and the like.
  • third party service providers 1 1 1 may be an input 112 to the system 104 and user interface 102.
  • Third party service providers 1 1 1 may be integrated into the system 104 to enable users to make the best personalized product or service selection for their hair, skin, nails, and the like for medical or cosmetic / beauty needs, and the like.
  • Third party service providers 11 1 may include hospitals, physicians, spas, salons, aestheticians, beauticians, cosmetic counters, drug stores, cosmetics sales representatives and websites, ranking and rating services, product information databases, testing laboratories, magazines and information providers, insurance companies, social networking sites, health and wellness services, photograph enhancement services, and the like.
  • the scheduling system for a physician may be integrated and scheduling options offered online to users, while also connecting with insurance providers to confirm coverage with the user.
  • pre-assessments on the condition, availability of historical medical and/or cosmetic products prescribed either over the counter or by medical prescription, and / or recommended services may be captured to make the selection process for the user convenient and easy.
  • a system for providing recommendations for skin care based on a skin state 158, a skin care goal, and environmental factors affecting the skin may comprise obtaining a skin state 158 of an individual, categorizing the individual by skin state 158, and recommending products and regimens that may be effective in achieving a skin care goal.
  • the system may be computer-based, Internet based, network based, and the like.
  • the system may be a community-led provision of skin services.
  • the recommendation may be made on the basis of identifying other users with similar skin states and identifying a product or regimen that is effective for them.
  • the recommendation may be made on the basis of product information 190, wellness information 192, a third party database 1 15, an expert 105, a service provider 1 1 1 , and the like.
  • a user may acquire an initial image and perform an analysis for a specific endpoint, such as moisture in this case.
  • the system may automatically recommend certain products based on the moisture level that may be effective given the moisture level, a skin state 158, and the like. Additionally, the system may perform a projection of skin state 158 based on various skin care regimens 1 18, such as maximum care, normal care, or poor care.
  • the images may be captured using the device 108 or third party hardware 109.
  • Images may be captured using any image capture device or technique, employing any kind of incident light, such as unpolarized light, polarized light, monochromatic light, diffuse light, white light, multiple single wavelength light, and the like. Any captured image may be used to obtain a skin state 158.
  • An embodiment of a skin care recommendation page of a skin care system may include a report of products the user is currently using, user input to obtain a skin state 158, a recommendation request, and the like.
  • the report on the products the user is currently using may include ranking or ratings 138.
  • a user accesses the user interface 102, they may access an adaptive questionnaire to determine their experience with their current regimen 1 18, current products or therapies used, or any products or regimens 118 used in the past. For example, the user may be asked to respond to questions such as How effective is it?, How is its fragrance?, How does it absorb?, Does it cause breakouts?, How does it feel?, Do you think this product is of good value?, and the like.
  • rankings and ratings need not be prompted by questions but may simply be anecdotal, deployed in a non-question format, deployed in a drop down menu, and the like.
  • the user may enter data relating to aspects such as gender, age, ethnicity, location, skin color, environmental factors, and the like.
  • analysis 154 of images obtained from the device 108 or third party hardware 109 may also be used to determine a skin state 158.
  • users may be able to determine products and regimens 118 that may work best for their skin state 158 by connecting to a database containing wellness 192, regimen 118, expert 105, service provider 1 1 1 , and product information 190, wherein the information may comprise product ingredients, product claims, product indications, product pairing, product usage protocol, product ratings and rankings 138, and the like.
  • rankings and ratings 138 community-led recommendations may be made for skin related products adjusted for age, skin color, location, ethnicity, environmental factors, and the like.
  • the user may perform a recommendation request which may involve selecting a skin goal, such as moisturize, protect, cleanse, tone, beautify, anti-aging, wrinkle protection, skin tightening, deep cleanse, pore diminishing, treat rosacea, exfoliate, lighten skin, tan, sun protect, self-tan, treat acne, avoid pimples, improve luminosity, skin rejuvenation, treat spots, treat Crow's feet, hair removal, scar treatment, and the like.
  • a skin goal may be automatically selected by the system 104. Automatic selection may be based on an aspect of the skin state 158.
  • the system may recommend moisturizing products for severely dry skin, or the system may recommend ingredients to look for in a product.
  • the user may be able to purchase products directly from the recommendations page, such as by placing the product in an electronic shopping cart 1 13, or may be directed to another site for purchase.
  • the user may add the product to a wish list 119 for future purchasing.
  • the user may add the product to a skin care shelf 114, which may be an interface to or depiction of a regimen 118 that enables users to organize their products and regimen 1 18 in a logical fashion based on the user's specific skin characteristics 130, by usage scenario (e.g. Morning, afternoon, night, etc.), intent (e.g.
  • the beauty shelf 114 may have multiple screens for recommendations by various bodies (e.g. Physicians, dermatologists, aestheticians, spa specialists, overall users, experts, people most like you, etc.).
  • the beauty shelf 1 14 may be a personalized arrangement of products. Users may drag and drop products (or select to add) as they are surfing the web and discover new products as well as having auto-populated recommendations. The functionality may include a program that will highlight products of interest while surfing the web.
  • the beauty shelf 1 14 may be an application that can also sit independently on social networking sites and other personal pages and or toolbars.
  • the beauty shelf 1 14 may also indicate purchase date and purchase history, product expiration alerts and other usage updates. A purchase made off the website may automatically add to the user's beauty shelf 1 14, while manual entries for offline purchases may also be possible.
  • the user may be able to obtain samples of recommended or non- recommended products directly from the recommendations page.
  • the shopping cart 1 13 may be a functionality that integrates with the skin care shelf 1 14. Users may be able to use the personalized recommendations and select products either for purchase, or for sample delivery. The user may be prompted for personal information such as address, shipping method, credit card number and the like, and that information may be retained by the shopping cart 113.
  • the shopping cart 1 13 may be an independent program, in similar fashion to the skin care shelf 1 14, that may reside in a toolbar, as part of a user interface 102 or as a program on a webpage, so that products could be highlighted and dragged into the shopping cart 1 13 for later purchase. Dragging the product into the cart 1 13 may also initiate queries across the database and across various websites for best price, location and availability of product, consumer experience, rankings and ratings and the like.
  • a product rating page of a skin care system is depicted.
  • users may be asked to respond to their medical, non-medical, cosmetic and skin care product experiences, thereby scaling data collection inexpensively.
  • a user may identify a product and provide an effectiveness assessment, rankings and ratings 138 for the product, anecdotal information, usage information, and the like. This information may be stored in a wellness 192, regimen 118, and product information 190 database in order to refine future recommendations.
  • user responses to product experiences may be shared with friends and/or other users automatically or upon request.
  • a user interface 102 home page 1000 of a skin care system 104 is depicted.
  • the user may be prompted to input demographic information such as name, gender, age, occupation, ID, address, telephone number, email address, payment information, new related users, and the like, which may be stored in a user profile or as part of a skin record 121 .
  • the home page may show a skin record 121 , or a listing of areas imaged, date imaged, and status of analysis.
  • an icon may be displayed near the Status.
  • the user may be able to launch a new Skin Health Test from the home page 1000 or submit a new skin concern.
  • the user may be able to forward the analysis 154 to an interested party; Ask an Expert a question regarding an aspect of the skin, skin history/record 121 , image analysis, and the like; view payment information and history; and the like.
  • a welcome page 1 100 of a skin health test is depicted.
  • the welcome page may provide information on the skin health test, what endpoints will be tested for, such as elasticity, wrinkles/ fine lines, sun damage, glow / luminosity, and the like.
  • the system may provide a personalized assessment of the user's skin regimen 1 18.
  • the user may initiate the skin health test from the welcome page 1100.
  • a questionnaire page 1200 of a skin care system is depicted.
  • the questionnaire may capture relevant skin history that may be useful for subsequent image analysis.
  • the questions may be asked in multiple choice fashion or as open-ended questions. For example, a question may be 'Where do you use your product?' with responses including face, hands, neck, legs, torso, and the like. Another question may be 'Why are you using your product?' with responses including to protect, repair, moisturize, and any other skin care goal. Another question may be, 'Why are/will you be using your product?' with responses including reduce wrinkles / fine lines, increase shine / luminosity, increase softness / elasticity, and any other skin care goal.
  • a skin image capture page 1300 of a skin care system is depicted.
  • the user interface 102 may access a device 108 in order to capture images, however, it should be understood that other devices 109 may be conveniently used in the system.
  • the page 1300 may show a real time view of the area being imaged.
  • the user may be able to employ positioning tools to be able to take an exact image of an area previously imaged.
  • an algorithm 150 may verify the integrity of the image. Once an image suitable for analysis has been captured, the user may proceed to an analysis page 1400.
  • Algorithms 150 may be used to analyze the image and provide measurements of wrinkles, elasticity, luminosity, firmness, tightness, and the like, as described previously herein.
  • the measurements may be quantitative measurements.
  • the first analysis may be considered a baseline for purposes of tracking.
  • the user may be compared against the baseline for their age, skin state, gender, ethnicity, or any other category.
  • the graph depicts the reading for the user in the first bar on each graph and the average baseline for people of the same age in the second bar. It is apparent from visual inspection that the user is better than average, in this case.
  • the results page 1400 may include a description of each measure.
  • the user may be able to request More Information for each of the measures, such as why a certain condition is caused and hints and tips on how to improve a skin condition.
  • the user may be given instructions on when to re-scan the area, which products to use, which regimen 118 to employ, and the like. Desired improvements may be correlated to ingredients and most effective products for the user's skin may be recommended.
  • the user may access and/or edit a skin record 121 , which may contain information about the user, images, a chronology of images, information derived from the images, recommendations, products, regimen 118, and the like.
  • the user may access a report facility to obtain a report.
  • a method for tracking the effectiveness of a skin care product or regimen may comprise obtaining a baseline skin health assessment; recommending a monitoring interval based on at least one of the skin care goal, product, and regimen; obtaining a second skin health assessment; comparing the second assessment to the baseline assessment to determine progress towards a skin care goal; and, optionally, optimizing the regimen 1 18 or product in order to improve a skin health assessment.
  • a trend analysis may be performed.
  • Subsequent images may be used to track effectiveness of products and/or regimens 1 18 and, ultimately, advise the user on and optimize their skin regimen 1 18, product and/or condition.
  • the trend analysis 1502 may be useful for determining an intermediate skin state 158 during a regimen 118.
  • the trend analysis 1502 may show a baseline reading, an average reading for healthy skin for someone of the user's age, and individual measurements for each type of skin condition. Progress may be shown over time.
  • a time series of images such as over a twenty-eight day skin cycle, over a treatment timeframe, seasonally, periodically over a year and the like may be captured in order to track progress of a skin state 158.
  • the data may be presented in a pictorial view with data on the picture, graphical view, trend view, numerical view, text view, and the like. Progress may be sorted by the concerns / skin care goals that the user may have indicated at the beginning of the test. The user may be told when to take the next image, how much longer to continue with a regimen 1 18, how to modify the regimen 1 18, be reassured about the effectiveness of a product or regimen 1 18, receive useful tips, and the like.
  • the user may view and/or edit a skin record 121 . The user may be able to view past images and perform a simulation 132 of future progress. The user may access a report facility to obtain a report.
  • a summary screen of a skin care system is depicted.
  • An overall analysis for a time interval may be shown, current measurements, progress towards reaching a skin care goal, a product assessment, a regimen 1 18 assessment, advice on continuing, modifying, or terminating a regimen 1 18 or product usage, and the like.
  • the user may view a step-by-step analysis or obtain a full report.
  • a report may include information on how the user's skin state 158 changed over time, if the user's skin is healthier than when they started the regimen 1 18, if the product or regimen 118 met their initial goals, feedback on regimen 118/ product effectiveness, and the like.
  • a new product or regimen 1 18 may be recommended.
  • the system may recommend specific ingredients to look for in order to increase a user's luminosity given a current skin state 158.
  • Reports may be on-screen, printed, custom, and the like. Reports may be shared with a practitioner for ongoing treatment and consultation.
  • an elasticity summary page 1700 of a skin care system is depicted.
  • a step- by-step analysis of each indicator may be performed.
  • a step-by-step analysis of the elasticity measurement is shown in Fig. 17.
  • the summary page 1700 may depict all of the data captured over an interval, such as in a bar graph, for each indicator on separate summary pages 1700. It should be understood that while Fig. 17 depicts an elasticity summary page, the summary page may summarize data related to any and all concerns.
  • Progress towards meeting a skin care goal may be indicated by the data and its analysis or from user input.
  • An assessment of a user's product or regimen 1 18 in meeting the skin care goal may be made.
  • Products or regimens 118 that may enable meeting future needs may be indicated.
  • the system may also indicate products used or regimens 1 18 employed by other users in meeting the stated skin care goal.
  • the data acquired at a single time point or over a time interval may be shared with other users of the skin care system, practitioners, and the like.
  • the data may be shared as a data object with users of an online platform 120 or mobile platform 124 of the skin care system, posted to blogs, e-mailed to third parties, and the like.
  • the data may be a drag-and-droppable data object.
  • the wrinkle trend analysis 1502 shown in Fig. 15 may be shared with friends as in Fig. 68, posted on a blog or forum where users may discuss the data as in Fig. 69, become part of the content that a user may wish to discuss as in Fig. 70, and the like.
  • a system for providing recommendations for skin care based on a skin state 158, a skin care goal, and environmental factors affecting the skin may comprise interaction with tools and algorithms 150 on an online platform 120, a mobile platform 124, a social networking interface, and the like to receive product and regimen recommendations and track product and regimen 1 18 effectiveness.
  • the system may be a communication platform, online 120 or mobile 124, that connects geographically separate consumers, manufacturers, product information, experts, service providers and others related to or allied to the beauty and medical field to provide personalized assessment regarding the consumers skin, hair, or nails queries and concerns.
  • the user interface 102 may reside on an online platform 120, mobile platform 124, or social networking interface.
  • a skin care assessment may be provided by algorithms 150 operating on an online platform 120 without the use of images or data from a device 108, that is, a user need not have data from a device 108 to participate in the online platform 120.
  • the online platform 120 may be a standalone skin health assessment and skin care recommendation tool.
  • image data may also be used by the online platform 120 to provide skin health assessments and skin care recommendations.
  • a user interface 102 may interface with the online platform 120.
  • a user may access an online platform 120 of the system for skin health analysis, monitoring, and recommendation to: monitor skin health, download, process, analyze, track, and store data from an imaging device 108 or other device 109 or monitor 182, receive product and /or regimen recommendations from an analysis/ API 154 or from peers, compare skin state 158 and regimen 1 18 with peers, receive product information 190, purchase products; add recommendations to a skin care shelf 114; organize a skin care shelf 1 14 by regimen 1 18, rankings, expiration date, cost, skin care goal, time of day, frequency, friends, and the like; view community ratings, rankings and comments on products/ regimen in a skin care shelf 1 14; rank/rate products; leave comments on products, regimens, peers products and/or regimens; and the like, receive new product alerts or product recalls, receive a daily report 134, interact with a social network 188, and the like.
  • the user interface 102 may enable users to conveniently take and submit images, enter data, track history, obtain recommendations and analysis and perform a purchase regarding their skin, hair, and/or nail's beauty/cosmetic or medical concern.
  • the user interface 102 may reside on an online platform 120 and guide the user while also serving as a data repository to maintain a skin record 121 and history tracking tool, and may help the user organize information relevant to their condition in a logical fashion.
  • the user interface may comprise a skin care shelf 114.
  • the skin care shelf 114 may be a structure that enables users to organize their products and regimen 118 in a logical fashion based on users' specific skin characteristics 130 / skin state 158 by usage scenario (such as morning, afternoon, night, and the like), intent (such as work, fun, etc.), skin care goal (such as moisture, glow, protect, and the like), and the like.
  • the skin care shelf 1 14 may have multiple "pages" for recommendations by various entities (such as practitioner, physicians, dermatologists, aestheticians, spa specialists, overall users, experts, people most like you, and the like).
  • the skin care shelf 1 14 may be a personalized arrangement of products, regimen 1 18, and/or information 190, 192.
  • a plug-in 194 may be used to allow a user to capture information from any location on the Internet.
  • a user may access a web page for a makeover article in a beauty magazine and wish to include the products from the makeover in their skin care shelf 1 14 and/or shopping cart.113.
  • the user may click on the product name and drag it over to at least one of the skin care shelf 1 14 and shopping cart 1 13 to obtain additional product information 190, include in their regimen 1 18, purchase, request samples, and the like.
  • the skin care shelf 1 14 may an application that may also sit independently on social networking sites 188 and other personal pages and or toolbars.
  • the skin care shelf 1 14 may also indicate purchase date and purchase history, product expiration alerts and other usage updates.
  • a purchase made off a website may automatically add to the users' shelf 1 14, while manual entries for offline purchases may also be possible.
  • the user interface 102 may interface with a mobile platform 124.
  • the user interface 102 may support plug and play with various mobile devices 184 such as mobile phones, laptops, digital cameras, medical-use devices, and the like.
  • the mobile phone may have an attachment or an integrated feature that may enable a user to take an image of the skin and input/ capture data and have it connect via the web, wirelessly or via cable, to the user interface 102 and enable seamless connectivity and data transfer.
  • the mobile device could be used to take images and data at various locations for obtaining various information from the community (such as at the beach to measure effectiveness of sun screen, an image of a specific location, a product image or a bar code image to get product feedback, best price, nearest physical selling location, coupons, and the like).
  • the mobile device could have an internal lens system that may be internally charges or an independently attached lens system that would enable using the battery power and light source of the device to take an image and use the in-built communication method for submitting the image.
  • the user interface for the online platform 120 may be depicted as a map.
  • the home page may have a different theme or feel depending on the user profile, the user preference, or any other criteria. For example, it may be fun, serious, clinical, and the like.
  • a user may review products, contribute anecdotes, report, review reports, review blogs by product, skin type, and the like, visit their beauty shelf 1 14, and the like. Information may be accessed freely, with registration, or only partially freely and partly with registration. All products and pages may link through the beauty shelf 114.
  • Fig. 19 depicts a review page of the user interface of a skin care system.
  • the menu across the top of the user interface may enable a user to access Reviews, Experience, Recommendation, Info For Me, Checkout, and the like.
  • the user interface may depict a portion of the user profile, such as the age, gender, location, skin type, skin color, skin goal, picture, and the like for the user.
  • the user interface may also depict what products or regimen 118 the user may be using and any associated review, rating, or comments of the product. Other users accessing a user profile may make comments on the regimen 1 18 or products in use, give the products or regimen 1 18 a rating, recommend a different product or regimen 1 18, and the like.
  • the user interface may present tools to aid a user in selecting a product or regimen 1 18.
  • the tools may be in the form a questionnaire or wizard guising the user to describe their skin.
  • the user may provide age, gender, skin type (oiliness, sensitivity), skin color, goal, current brand or product, current regimen 1 18 and the like.
  • the skin type and/ or color may be detected automatically if the user interface is interfaced with an imaging device 108.
  • the user may also access their beauty shelf 114 from the user interface.
  • a review page of a user interface of a skin care system is depicted.
  • the review page is shown in a different layout than the compact view depicted in Fig. 19.
  • an experience page of a user interface of a skin care system is depicted.
  • the experience page allows users to provide a detailed report of experience with a product or regimen 118.
  • the user may note the effectiveness of a product or regimen 118, such as by answering questions.
  • the questions may be "How effective is it?", “How does it feel?”, “How is its fragrance?”, “How does it absorb?”, “Does it cause breakouts?”, and the like.
  • the experience page may also allow a user to update a user profile with age, gender, nickname, location, a photo, skin type, skin color, goal, and the like.
  • the user may be able to query other users for their experience or make a general inquiry by submitting a request to an email, MMS, SMS, phone number, mobile device, social network, and the like.
  • a recommendation page of a user interface of a skin care system is depicted.
  • various products or regimens 1 18 that may be effective in meeting the goal may be shown on the recommendation page.
  • the brand and product or regimen 1 18 may be shown along with a rating from the community of users, comments from users, the ability to indicate of the user believes the product may better than the current product or regimen 1 18 in use, and the like. If the user believes the product or regimen 1 18 may be better than what they are currently using, the product or regimen 1 18 may be stored for future consideration on the beauty shelf 114.
  • a People Like Me algorithm 150 may be used to sort the community of users of the skin care system. Given the aspects of the user profile, the algorithm 150 may determine which other users are most similar along all criteria, along custom-selected criteria, along a combination of skin color and skin type, and the like. Once the algorithm 150 has determined a subset of the community of users who are most like the user, the user can view data for the community. For example, the user can find out which products work best for the subset generally, for a specific issue, for a specific time of day, for a specific season, and the like.
  • the Info for Me page may also depict the weather for the location given in the user profile and a UV rating and any specific tips given the location / weather/ environment.
  • the Info for Me page may also alert the users of new products being launched. The user may sort the products according to effectiveness.
  • FIG. 24 an example of a beauty shelf 1 14 portion of a user interface of a skin care system is shown.
  • Products or regimens 1 18 used by the user may be categorized by time of day use, specific effectiveness, cost, expiration, and the like. Each item may be clicked on to pop-up additional details about the product or regimen 1 18, such as effectiveness, ingredients, suggested use, expiration date, a link to purchase more, a link to blog about the product or regimen 118, a link to write a review or read reviews, a link to the manufacturer's site, a link to an in-store coupon, and the like.
  • Fig. 25 depicts another example of a beauty shelf 1 14 portion of a user interface of a skin care system.
  • 26 depicts an alternate view of the beauty shelf 1 14 of the user interface of a skin care system.
  • friends have the ability to comment on the products or regimen 1 18 and suggest an alternative product or regimen 118.
  • the user also has the option to receive price alerts, new product launch alerts, new user comment alerts, and the like.
  • a registration page of a user interface of a skin care system is depicted.
  • Information may be entered by the user, goals may be indicated, a security code may be entered, skin concerns, color, and/or type may be entered, samples may be registered for, and the like.
  • the user may indicate that the want to add a feed from the skin care system to their RSS feed, and application from the skin care system to a social networking site, and the like.
  • the user may have the option to opt-in to alerts, to be notified of samples and products, and the like.
  • FIG. 28 another embodiment of a recommendation page of a user interface of a skin care system is shown.
  • This page may show people in the user's category, such as number of people of the same gender, same age group, with similar skin type, with similar concerns, and the like.
  • people in the user's category such as number of people of the same gender, same age group, with similar skin type, with similar concerns, and the like.
  • a product may be recommended that is most popular, has the most buzz, has been reviewed, has been rated, has been blogged about, and the like.
  • the user interface may include a friend toolbar.
  • the friend toolbar may float over a current website, or any website, such as by using a plug-in. Friends may upload images and the images 6408 may be displayed on the friend toolbar 6402.
  • a home key 6404 may be part of the toolbar 6402, where the whole toolbar can be reduced to just the home key 6404.
  • a flag alert 6410 may pop-up next to their image on the toolbar 6402.
  • a bottom bar 6412 may be used for shuffling friends or accessing other options related to the toolbar 6402. Referring to Fig.
  • the toolbar 6402 may auto-scroll 6502 as the user scrolls the webpage they are viewing.
  • objects may be shared with friends in the friends' toolbar 6402 using a drag-and-drop functionality 6602.
  • a blog posting may be shared as in Fig. 66 by dragging and dropping the blog title onto a friend's image.
  • products may be recommended to a friend by dragging and dropping 6702 the product into the friends' image, as in Fig, 67.
  • Rolling over a friends' image may result in a pop-up, dialog box or other manifestation of additional information about the friend, such as a view of their user profile, beauty shelf 1 14, reviews, blogs, and the like.
  • a mobile content map for a mobile user interface of a skin care system on a mobile platform 124 is depicted.
  • the content map depicted shows an example of content that can be accessed from a mobile platform 124 home page.
  • a product may be scanned or identified from a list and searched for using the internet on the mobile device.
  • a bar code may be scanned for a product and prices, reviews, ratings and the like for the product may be returned.
  • the user may be helped to find something, such as an item for themselves, a gift for a friend, and the like.
  • the product may be searched for based on a goal, an issue, a skin type, a skin color, and the like.
  • the mobile skin care system may return a list of products, such as the top 10 products, and information about the products such as rating, impact on goals, safety, reviews, and the like.
  • the user may access a Suncheck application to be given UV information by location and advice, as well as based on an image captured by an imaging device 108 embodied in a mobile device, as described previously herein.
  • a bar code may be scanned to obtain product info, the bar code numbers may be manually entered, or the product may be chosen from a list.
  • the system may return product information such as the product name, rating, ingredients, a general rating, a rating for a specific concern, a friend's rating, a price, where the product can be found, and the like. If the mobile device is enabled, a purchase may be initiated on the mobile platform 124.
  • a What Should I Look For? message flow is depicted.
  • the message flow may begin by giving the user the option to indicate if the item searched for is a gift, for the user, to update a pick list, and the like.
  • a recipient may be selected from a pre-populated list or a new recipient may be indicated.
  • An occasion may be indicated.
  • products may be recommended along with any information associated with the product, a price, a location, and an option to purchase on the mobile platform 124.
  • the user may indicate a goal, such as from a drop down menu, and receive a list of recommended products.
  • the user may request to locate the product at a store or initiate a purchase on the mobile platform 124, or the like.
  • a Suncheck message flow is depicted.
  • the initial message may contain information about the user's location, the weather, a UV index, a sun impact rating, an indication of the maximum exposure time, and a timer for measuring the current time in the sun. Advice may be generated based on the information, such as what level of sun protection factor to apply, a maximum recommended time of exposure, and the like.
  • an Alert message flow is depicted.
  • the user may be linked to other users on the mobile platform 124 so that when another user requests a review or rating of a product, an alert may be sent to the user.
  • the user may respond with a review, a rating, a chat message, an SMS, an MMS, a phone call, a voicemail, and the like.
  • Options 3404 may be a friend list, a pick list, alerts, address/location, and the like.
  • Options 3404 may be a friend list, a pick list, alerts, address/location, and the like.
  • a friend list 3408 may be accessed to pick and choose friends to follow, receive alerts from and the like.
  • the friends list may indicate if the friend is online.
  • Alerts 3410 may also be set on the mobile platform 124, for example to notify the user when their friends buy something new, notify the user when a new product that is good for them is available, and the like.
  • Address / location / payment setup may allow the user to initiate purchases from the mobile platform 124.
  • systems and methods for analysis of skin diseases (or disorders) by image processing detection (or image processing-based detection) of dermascopic structures (or skin lesions) are disclosed. More particularly, there is disclosed the design and implementation of a system for automated diagnosis of seborrheic keratosis by image processing detection of multiple milia-like cysts or comedo-like openings and methods thereof.
  • an improved system with enhanced qualitative and quantitative parameters such as non-invasive, automatic, reliable, accurate and easily operable, for automated diagnosis of seborrheic keratosis by image processing detection of multiple milia-like cysts or comedo-like openings and methods thereof and a method for the design and implementation of such a system.
  • FIG. 71 is a schematic view of a system for automated diagnosis of skin disorders by image processing detection of skin lesions or dermoscopic structures, designed and implemented in accordance with at least some embodiments of the invention.
  • the system 7100 is in essence an Automatic Seborrheic Keratosis Diagnosis System (or ASKDS).
  • ASKDS Automatic Seborrheic Keratosis Diagnosis System
  • the ASKDS 100 consists of an illumination subsystem 7102, a sensor subsystem 7104 and a host computing subsystem 7106.
  • the ASKDS 100 by virtue of its design and implementation, facilitates automatic diagnosis of seborrheic keratosis based on detection of multiple milia-like cysts or comedo-like openings through image processing.
  • the ASKDS 7100 for automated diagnosis of skin disorders and processes thereof has been disclosed.
  • the ASKDS 7100 comprises one or more illumination sources.
  • the illumination sources comprise incident light sources to direct light upon skin.
  • the incident light sources may be unpolarized or polarized light sources.
  • the unpolarized light may be white light, multiple selected wavelengths, or a single wavelength.
  • the illumination source may be positioned to direct light at a selected angle alpha.
  • the ASKDS 7100 implements the processes for non-invasive processing including, but not limited to, imaging, analysis, and the like, as disclosed in United States Provisional Patent Applications "METHOD AND ALGORITHM FOR ANALYSIS OF LIGHT-MATTER INTERACTION BASED ON SPECTRAL CONVOLUTION” and “IMAGING DEVICE UTILIZING WHITE LIGHT FOR COMPSOITION ANALYSIS” and United States Non-Provisional Patent Applications "SYSTEM, DEVICE, AND METHOD FOR DERMAL IMAGING” to MYSKIN, INC., the disclosure of which is incorporated herein by reference in its entirety.
  • SYSTEM, DEVICE, AND METHOD FOR DERMAL IMAGING to MYSKIN, INC.
  • the illumination subsystem 7102 may be coupled to the sensor subsystem 7104.
  • the sensor subsystem 7104 may in essence be a device that converts optical images (or optical signals) to electric signals.
  • the sensor subsystem 7104 captures continuous digital images of skin.
  • the sensor subsystem 7104 captures continuous digital images of the metallic surface illuminated with white light both, non-angled and angled.
  • the sensor subsystem 7104 may be anyone selected from a group consisting of a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor, Charged Coupled Device (CCD) image sensor, and the like.
  • CMOS Complementary Metal-Oxide-Semiconductor
  • CCD Charged Coupled Device
  • the sensor subsystem 7104 may be coupled to the host computing subsystem 7106 and the illumination subsystem 7102, respectively.
  • digital image refers to a representation of a two-dimensional image using ones and zeros (or binary digits or bits).
  • the digital image may be of vector or raster type depending on whether or not the image resolution is fixed. However, without qualifications the term “digital image” usually refers to raster images.
  • digital imaging or digital image acquisition refers to creation of digital images, typically from a physical object. The term is often assumed to imply or include the processing, compression, storage, printing and display of such images.
  • Digital image processing is the use of computer algorithms to perform image processing on digital images. As a subfield of digital signal processing, digital image processing has many advantages over analog image processing; it allows a much wider range of algorithms to be applied to the input data, and can avoid problems such as the build-up of noise and signal distortion during processing.
  • the sensor subsystem 7104 may be selected on the basis of the following specifications: color is color or monochrome; optical format; horizontal pixels X vertical pixels; pixel size; one or more performance parameters, such as maximum frame rate, data rate, maximum power dissipation, quantum efficiency, dynamic range and supply voltage; output; one or more features, such as integrated Analog-to-Digital Converter (ADC) and microlenses; and environment, such as operating temperature.
  • ADC Analog-to-Digital Converter
  • the host computing subsystem 7106 may comprise a skin disorder management module designed and implemented, in accordance with the principles of the invention.
  • FIG. 72 is an exploded diagrammatic representation of the host computing subsystem, of the Fig. 71 , comprising the skin disorder management module designed and implemented in accordance with at least some embodiments.
  • the host computing subsystem 7200 may comprise a processing unit 7202, a memory unit 7204 and an Input / Output (or I / O) unit 7206 respectively.
  • the host computing subsystem 7200 by virtue of its design and implementation, performs overall management of one or more disorders of skin.
  • the processing unit 7202 may comprise an Arithmetic Logic Unit (or ALU) 7208, a Control Unit (or CU) 7210 and a Register Unit (or RU) 7212.
  • ALU Arithmetic Logic Unit
  • CU Control Unit
  • RU Register Unit
  • the memory unit 7204 comprises a skin disorder management module 7214.
  • the skin disorder management module for real- or point-time analysis of the continuously captured digital skin information and methods thereof is disclosed, in accordance with the principles of the invention. Specifically, in such embodiments, the skin disorder management module captures the skin information using at least one of Diffused Reflectance Spectroscopy, Red (R)-Green (G)-Blue (B) analysis of re-emitted white light and any combination thereof.
  • Diffused Reflectance Spectroscopy Red (R)-Green (G)-Blue (B) analysis of re-emitted white light and any combination thereof.
  • DRS Diffused (or Diffuse) Reflectance Spectroscopy
  • DRIFTS Diffuse Reflectance Infrared Fourier Transform Spectroscopy
  • the skin disorder management module may comprise one or more processes for determination of an assortment of qualitative and quantitative parameters thereby facilitating overall management of disorders of skin.
  • at least a first process of the one or more processes determines moisture levels of skin.
  • this process may comprise one or more phases comprising emission of incident electromagnetic signals to skin, detection of degree of polarization of the electromagnetic signals reflected or re-emitted from skin and determination of the moisture levels based on the amount of polarized and reflected or re-emitted electromagnetic signals.
  • the first process may comprise one or more phases comprising combination of the determined moisture levels with skin color measurements thereby resulting in determination of skin luminosity.
  • At least a second process of the processes determines elasticity of skin.
  • this process may comprise one or more phases comprising the emission of the incident electromagnetic signals to skin, detection of a first aspect of polarization of the electromagnetic signals reflected by skin, correlation of the aspect of polarization with a concentration of elastin and determination of elasticity level based on the concentration of elastin.
  • At least a third process of the processes determines firmness of skin.
  • this process may comprise or more phases comprising the of the incident electromagnetic signals to skin, the detection of a second aspect of polarization of the electromagnetic signals reflected by skin, the correlation of the aspect of polarization with the concentration of at least one of the elastin, a collagen, an activity of a sebaceous gland and any combination thereof and determination of the firmness based on the concentration of at least one of the elastin, collagen and sebaceous gland activity.
  • the sebaceous gland activity may be indicated by at least one of a number of glands, percent of glands open / closed and level of clog / fill.
  • At least a fourth process of the processes obtains biophysical properties and may comprise performing a spectral analysis of image data acquired from the degree of polarization of reflections and absorption and re-emission of incident light from skin.
  • the biophysical properties is at least one of a structure, form, concentration, number, size, state, and stage of at least one of a: melanocyte, melanin, hemoglobin, porphyrin, keratin, carotene, collagen, elastin, sebum, sebaceous gland activity, pore (sweat and sebaceous), moisture level, elasticity, luminosity, firmness, fine line, wrinkle count and stage, pore size, percent of open pores, skin elasticity, skin tension line, spot, skin color, psoriasis, allergy, red area, general skin disorder or infection, tumor, sunburn, rash, scratch, pimple, acne, insect bite, itch, bleeding, injury, inflammation, photodamage, pigmentation, tone, tattoo, percent burn/ burn classification, mole (naevi, nevus), aspect of a skin lesion (structure, color, dimensions/asymmetry), melanoma, dermally observed disorder, cutaneous lesion, cellulite, boil, blistering disease,
  • the skin disorder management module facilitates acquisition of dermal biophysical properties.
  • the skin disorder management module 7214 comprises a Fourier transform sub-module 7216, a spectral analyzer sub-module 7218 and a diagnostics sub-module 7220.
  • the Fourier transform sub-module 7216 is in essence a Discrete-Time Fourier Transform (or DTFT).
  • DTFT refers to one of the specific forms of Fourier analysis. As such, it transforms one function into another, which is called the frequency domain representation, or simply the "DTFT", of the original function, which is often a function in the time-domain. But, the DTFT requires an input function that is discrete. Such inputs are often created by sampling a continuous function, like a person's voice.
  • the DTFT frequency-domain representation is always a periodic function. Since one period of the function contains all of the unique information, it is sometimes convenient to say that the DTFT is a transform to a "finite" frequency-domain (the length of one period), rather than to the entire real line.
  • the DTFT 7216 converts time-domain digital signals into corresponding frequency-domain digital signals. [00576] The DTFT 7216 is coupled to the spectrum analyzer sub-module 7218.
  • the term "spectrum analyzer” refers to a device used to examine the spectral composition of some electrical, acoustic, or optical waveform. It may also measure the power spectrum.
  • spectrum analyzers there are three types of spectrum analyzers, such as analog, digital and real-time spectrum analyzers. Firstly, an analog spectrum analyzer uses either a variable band-pass filter whose mid- frequency is automatically tuned (i.e. shifted, swept) through the range of frequencies of the spectrum to be measured or a superheterodyne receiver, wherein the local oscillator is swept through a range of frequencies.
  • a digital spectrum analyzer computes the Discrete Fourier transform (or DFT), a mathematical process that transforms a waveform into the components of its frequency spectrum.
  • DFT Discrete Fourier transform
  • some spectrum analyzers such as "real-time spectrum analyzers" use a hybrid technique where the incoming signal is first down-converted to a lower frequency using superheterodyne techniques and then analyzed using fast Fourier transformation (FFT) techniques.
  • FFT fast Fourier transformation
  • the illumination subsystem 7102 illuminates the skin. It may be noted here that all ins-and-outs in connection with the illumination subsystem 7102 has been disclosed earlier and thus will not be detailed herein.
  • the sensor subsystem 104 captures the electromagnetic signals reflected, absorbed and re-emitted from the skin. As mentioned earlier, the ADC integrated in the sensor subsystem 7104 converts the analog electromagnetic signals into corresponding digital signals.
  • the skin disorder management module 7214 of the host computing subsystem 7106 facilitates automated diagnosis of seborrheic keratosis based on detection of multiple milia-like cysts or comedo-like openings through image processing.
  • the DTFT 7216 converts time-domain digital signals into corresponding frequency-domain digital signals.
  • the spectrum analyzer sub-module 7218, of the skin disorder management module 7214 performs a spectral analysis of the corresponding frequency-domain digital signals.
  • the diagnostics sub-module 7220, of the skin disorder management module 7214 detects the presence of one or more skin lesions or dermascopic structures, such as milia-like cysts or comedo-like openings through implementation of suitable image processing algorithms.
  • the host computing subsystem configuration implements one or more processes facilitating acquisition of biophysical properties of organ systems, analysis of characteristics of the organ systems and determination of a state of the organ systems.
  • the processes comprise one or more sequences of process stages comprising acquisition of dermal biophysical properties of skin, analysis of the skin characteristics and determination of a skin state and potential permutations and combinations thereof.
  • a customized image processing algorithm (not depicted herein), designed and implemented in accordance with the principles of the invention, may be useful for the analysis of skin characteristics, obtaining the biophysical properties of the skin and determining a skin state.
  • the skin state may capture a combination of underlying skin structure with time-based variance. Some variation may be predictable but some may be based on a transient condition like infection, sunburn, hormonal imbalance, and the like.
  • the algorithm may be able to measure aspects such as the structure, form, concentration, number, size, state, stage, and the like of melanocytes / melanin, hemoglobin, porphyrin, keratin, carotene, collagen, elastin, sebum, sebaceous gland activity, pores (sweat and sebaceous), wrinkles, moisture, elasticity, luminosity, all forms of the aforementioned, such as derivatives, salts, complexes, and the like.
  • the algorithm may be used to make a quantitative assessment of clinical, medical, non-medical, and cosmetic indications, such as moisture level, firmness, fine lines, wrinkle count and stage, pore size, percent of open pores, skin elasticity, skin tension lines, spots, skin color, psoriasis, allergies, red areas, general skin disorders and infections, or other skin related concerns for the user such as tumors, sunburns, rashes, scratches, pimples, acne, insect bites, itches, bleeding, injury, inflammation, photodamage, pigmentation, tone, tattoos, percent burn / burn classification, moles (naevi, nevus), aspects of skin lesions (structure, color, dimensions / asymmetry), melanoma, dermally observed disorders and cutaneous lesions, cellulite, boils, blistering diseases, management of congenital dermal syndromes, (sub)-cutaneous mycoses, melasma, vascular conditions, rosacea, spider veins, texture, skin ulcers, wound healing, post-operative tracking,
  • the algorithm may also be useful for the analysis of and obtaining the physical properties and composition of hair, nails, biological substances, gaseous substances, food, wine, water, liquid, metal, non-metals, plastics, polymers, and the like. Either manually or as determined by an algorithm, a targeted wavelength or wavelengths may be employed for specific endpoint measurements.
  • FIG. 73 is a block diagrammatic view of a system facilitating implementation of an Opto-Magnetic process based on light-matter interaction using digital imaging for detection of EPV and CMV viruses in blood plasma samples, designed and implemented in accordance with certain embodiments of the invention;
  • FIG. 74 is an exploded diagrammatic representation of the host computing subsystem, of the Fig. 1 , comprising the Opto-Magnetic Fingerprint (or OMF) Generator module designed and implemented in accordance with at least some embodiments;
  • FIG. 75 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 1 and 2 thereby facilitating estimation of blood plasma type and properties (or characteristics) thereof and creation of a unique spectral signature;
  • FIGS. 76A and 76B depict a dual pair of typical digital images of samples, tested positive and negative for EBV and CMV, captured with diffuse white light (W) and reflected polarized light (P), in that order;
  • FIGS. 77A and 77B depict a first pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a first set of two patients subjected to a first test case for confirmation of EBV, namely "Case I: EBV-lgM", designed and implemented in accordance with certain embodiments of the invention;
  • FIGS. 78A and 78B depict a second pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a second set of two different patients subjected to a second test case for confirmation of EBV, namely "Case II: EBV-lgM", designed and implemented in accordance with certain embodiments of the invention;
  • FIGS. 79A and 79B depict a third pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a third set of two different patients subjected to a third test case for confirmation of EBV, namely "Case III: EBV-lgG", designed and implemented in accordance with certain embodiments of the invention.
  • FIGS. 80A and 80B depict a fourth pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a fourth set of two different patients subjected to a fourth test case for confirmation of EBV, namely "Case IV: EBV-lgG", designed and implemented in accordance with certain embodiments of the invention.
  • methods for detection of DNA viruses based on the interaction between matter and electromagnetic radiation and systems and apparatuses facilitating implementation of such methods are disclosed.
  • systems and apparatuses for practicing the principles of the invention are disclosed. More specifically, the systems and apparatuses facilitate implementation of an Opto-Magnetic method with enhanced qualitative and quantitative parameters for detection of Herpesviridae in blood plasma samples based on Opto-Magnetic properties of light-matter interaction.
  • the systems and apparatuses facilitate implementation of an Opto-Magnetic method with enhanced qualitative and quantitative parameters, such as novel, easily operable, rapid, economical, precise, timely and minute variation sensitive, for detection of EPV and CMV in blood plasma samples based on Opto-Magnetic properties of light-matter interaction.
  • the sample set is subjected to diagnosis using OMF method.
  • the preparation of digital pictures for OMF is made by usage of non-invasive imaging device that has previously been successfully used in biophysical skin characterization, such as skin photo type, moisture, conductivity, etc.
  • non-invasive imaging device that has previously been successfully used in biophysical skin characterization, such as skin photo type, moisture, conductivity, etc.
  • systems, devices and methods for non-invasive dermal imaging has been disclosed in US Pat. App. No. PCT/US2008/050438, Publication No: WO/2008/08631 1 , Publication Date: 2008-07-17 "SYSTEM, DEVICE AND METHOD FOR DERMAL IMAGING" to J. Bandic, Dj. Koruga, R. Mehendale and S. Marinkovich of MYSKIN, INC., the disclosure of which is incorporated herein by reference in its entirety.
  • all remaining ins-and-outs in connection with the process of generating the spectral signature will not be further detailed herein.
  • OMF Opto-Magnetic Fingerprint
  • the design and implementation of an Opto-Magnetic Fingerprint (OMF) process for detection of EPV and CMV in blood plasma samples has been disclosed.
  • the OMF process is based on electron properties of matter and its interaction with light.
  • the concept of light-matter interaction and Opto-magnetic thereof has been disclosed in United States Provisional Patent Application "METHOD AND ALGORITHM FOR ANALYSIS OF LIGHT-MATTER INTERACTION BASED ON SPECTRAL CONVOLUTION" to MYSKIN, INC., the disclosure of which is incorporated herein by reference in its entirety.
  • MYSKIN MYSKIN
  • valence electrons build a major link network of matter.
  • the orbital velocity of the valence electrons in atoms is on the order of 10 6 m/s.
  • the action of magnetic forces is four orders of magnitude closer to quantum action than the electrical ones.
  • the quantum state of matter is primarily responsible for conformational changes on the molecular level, this means that detecting differences between tissue states is by far more likely to give greater sensitivity on the level of magnetic forces than it would be on the level of measurement of electrical forces.
  • a macromolecular conformational change refers to a transition in shape of a macromolecule.
  • a macromolecule is flexible or dynamic. Thus, it can change its shape in response to changes in its environment or other factors. Each possible shape is called a conformation.
  • a macromolecular conformational change may be induced by many factors, such as a change in temperature, pH, voltage, ion concentration, or the binding of a ligand.
  • FIG. 73 is a block diagrammatic view of a system facilitating implementation of an Opto-Magnetic process based on light-matter interaction using digital imaging for detection of EPV and CMV viruses in blood plasma samples, designed and implemented in accordance with certain embodiments of the invention.
  • System 7300 is in essence a Virus Detection System (or VDS).
  • VDS 100 includes an illumination subsystem 7302, an imaging (or sensor) subsystem 7304 and a host computing subsystem 7306.
  • VDS 7300 facilitates execution of an Opto-Magnetic method based on interaction between electromagnetic radiation and matter, for instance light-matter interaction, using digital imaging for detection of EPV and CMV viruses in blood plasma samples.
  • the Opto-Magnetic process employs apparatuses for generation of unique spectral signatures from digitally captured images of blood plasma samples thereby facilitating detection of EPV and CMV viruses in blood plasma samples based on Opto-Magnetic properties of light-blood plasma interaction.
  • Illumination subsystem 7302 may be one or more electromagnetic radiation sources.
  • the Illumination subsystem 7302 may be a set of Light Emitting Diodes (LEDs).
  • Illumination subsystem 7302 may be adapted to emit polarized and unpolarized electromagnetic signals.
  • the polarized electromagnetic signal is angled white light and unpolarized electromagnetic signal is non-angled white light.
  • the illumination subsystem 7302 may be coupled to the sensor subsystem 7304.
  • the sensor subsystem 7304 may in essence be a device that converts optical images (or optical signals) to electric signals.
  • the sensor subsystem 7304 captures continuous digital images of blood plasma samples.
  • the sensor subsystem 7304 captures continuous digital images of the blood plasma samples illuminated with white light both, non-angled and angled.
  • the sensor subsystem 7304 may be anyone selected from a group consisting of a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor, Charged Coupled Device (CCD) image sensor, and the like.
  • CMOS Complementary Metal-Oxide-Semiconductor
  • CCD Charged Coupled Device
  • the sensor subsystem 7304 may be coupled to the host computing subsystem 7306.
  • FIG. 74 is an exploded diagrammatic representation of the host computing subsystem, of the Fig. 73, comprising the Opto-Magnetic Fingerprint (or OMF) Generator module designed and implemented in accordance with at least some embodiments.
  • OMF Opto-Magnetic Fingerprint
  • the host computing subsystem 7400 may comprise a processing unit 7402, a memory unit 204 and an Input / Output (or I / O) unit 206 respectively.
  • the host computing subsystem 7400 by virtue of its design and implementation, performs overall management of blood plasma samples.
  • the processing unit 7402 may comprise an Arithmetic Logic Unit (or ALU) 7408, a Control Unit (or CU) 7410 and a Register Unit (or RU) 7412.
  • ALU Arithmetic Logic Unit
  • CU Control Unit
  • RU Register Unit
  • the memory unit 7404 comprises a blood plasma virus detection module 7414.
  • the blood plasma virus detection module for detection of EPV and CMV via generation of unique spectral signatures from the digitally captured images of blood plasma samples and methods thereof are disclosed, in accordance with the principles of the invention.
  • the blood plasma virus detection module utilizes the continuously captured digital images of the blood plasma samples illuminated with white light both, non-angled and angled. More specifically, the blood plasma virus detection module takes into consideration the digital images in Red (R), Green (G) and Blue (B) (or RGB) system for purposes of analysis.
  • the blood plasma virus detection module 7414 includes a Fourier transform sub-module 7416, a spectral analyzer sub-module 7418 and an Opto-Magnetic Fingerprint Generator (or OMFG) sub-module 7420, respectively.
  • the Fourier transform sub-module 7416 is in essence a Discrete-Time Fourier Transform (or DTFT).
  • DTFT refers to one of the specific forms of Fourier analysis. As such, it transforms one function into another, which is called the frequency domain representation, or simply the "DTFT", of the original function, which is often a function in the time-domain. But, the DTFT requires an input function that is discrete. Such inputs are often created by sampling a continuous function, like a person's voice.
  • the DTFT frequency-domain representation is always a periodic function. Since one period of the function contains all of the unique information, it is sometimes convenient to say that the DTFT is a transform to a "finite" frequency-domain (the length of one period), rather than to the entire real line.
  • DTFT 7416 converts time-domain digital signals into corresponding frequency-domain digital signals.
  • DTFT 7416 is coupled to the spectrum analyzer sub-module 7418.
  • the term "spectrum analyzer” refers to a device used to examine the spectral composition of some electrical, acoustic, or optical waveform. It may also measure the power spectrum.
  • spectrum analyzers there are three types of spectrum analyzers, such as analog, digital and real-time spectrum analyzers. Firstly, an analog spectrum analyzer uses either a variable band-pass filter whose mid- frequency is automatically tuned (i.e. shifted, swept) through the range of frequencies of the spectrum to be measured or a superheterodyne receiver, wherein the local oscillator is swept through a range of frequencies.
  • a digital spectrum analyzer computes the Discrete Fourier transform (or DFT), a mathematical process that transforms a waveform into the components of its frequency spectrum.
  • DFT Discrete Fourier transform
  • some spectrum analyzers such as "real-time spectrum analyzers" use a hybrid technique where the incoming signal is first down-converted to a lower frequency using superheterodyne techniques and then analyzed using fast Fourier transformation (FFT) techniques.
  • FFT fast Fourier transformation
  • the spectrum (or spectral) analyzer sub-module for analysis of digitally captured images of blood plasma samples thereby facilitating detection of EBV and CMV is disclosed.
  • the spectrum (or spectral) analyzer sub-module in order to analyze the blood plasma samples takes into consideration digital images of blood plasma in Red (R), Green (G) and Blue (B) (or RGB) system.
  • basic pixel data in Red (R) and Blue (B) channels for both white diffuse light (or W) and reflected polarized light (or P) is selected.
  • the algorithm for data analysis is based on chromaticity diagram called "Maxwell's triangle" and spectral convolution.
  • the digital images in Red (R), Green (G) and Blue (B) (or RGB) system are taken into consideration for purposes of spectral analysis.
  • basic pixel data in Red (R) and Blue (B) channels for white diffuse light (or W) and reflected polarized white light (or P) is selected.
  • the algorithm for data analysis is based on a chromaticity diagram called "Maxwell's triangle" and spectral convolution operation, in accordance with a ratio of (R - B) & (W - P).
  • R Red
  • B Blue
  • W White light
  • P reflected Polarized light
  • the method and algorithm for creating unique spectral fingerprints are based on the convolution of RGB color channel spectral plots generated from digital images that capture single and multi-wavelength light-matter interaction for different paramagnetic materials, such as Al, Mn and Ti, diamagnetic materials, such as Cu, C and Zn, alloys, such asPbl-xMnxTe, Biomolecules and biological tissues as paramagnetic / diamagnetic materials, such as skin, biological water, amniotic fluid, blood plasma and the like.
  • incident white light can give different information about properties of thin layers of matter, such as a blood plasma sample surface, depending on the angle of light incidence. In use, when the incident white light is diffuse, the reflected white light is then composed of electrical and magnetic components, whereas diffuse incident light that is inclined under certain angle will produce reflected light which contains only electrical component of light.
  • the spectrum analyzer sub-module 7418 may be coupled to the OMFG sub- module 7420.
  • OMFG sub-module 7420 includes a color histogram generator unit 7422, a spectral plot generator unit 7424 and a convolution unit 7426.
  • OMFG sub-module 7414 by virtue of its design and implementation, facilitates generation of unique spectral signatures from digitally captured images of blood plasma samples. Specifically, the generated spectral signatures of blood plasma samples facilitate detection of EPV and CMV based on Opto-Magnetic properties of light-blood plasma interaction.
  • Color histogram generator unit 7422 by virtue of its design, generates a normalized Red (R) and Blue (B) color channel histogram for each of the one or more images of the blood plasma samples.
  • color histogram refers to is a representation of the distribution of colors in an image, derived by counting the number of pixels of each of given set of color ranges in a typically two-dimensional (2D) or three-dimensional (3D) color space.
  • a histogram is a standard statistical description of a distribution in terms of occurrence frequencies of different event classes; for color, the event classes are regions in color space.
  • An image histogram of scalar pixel values is more commonly used in image processing than is a color histogram.
  • image histogram refers to a type of histogram which acts as a graphical representation of the tonal distribution in a digital image. It plots the number of pixels for each tonal value. By looking at the histogram for a specific image a viewer is able to judge the entire tonal distribution at a glance.
  • color histograms are flexible constructs that can be built from images in various color spaces, whether RGB, rg chromaticity or any other color space of any dimension.
  • a histogram of an image is produced first by discretization of the colors in the image into a number of bins, and counting the number of image pixels in each bin.
  • the color histogram generator unit 7422 may be coupled to the spectral plot generator unit 7424.
  • Spectral plot generator unit 7424 generates Red (R) and Blue (B) color channel spectral plots by correlating the normalized Red (R) and Blue (B) color channel histograms to a wavelength scale.
  • a unit scale on the spectral signature is a difference of wavelength.
  • color digital images are made of pixels and, in turn, pixels are made of combinations of primary colors.
  • channel refers to the grayscale image of the same size as a color image, made of just one of these primary colors.
  • an image from a standard digital camera will have a red, green and blue channel.
  • a grayscale image has just one channel.
  • an RGB image has three channels, namely Red (R), Green (G) and Blue (B).
  • R Red
  • G Green
  • B Blue
  • the RGB image is 24-bit then each channel has 8 bits, for R, G and B.
  • the image is composed of three grayscale images, where each grayscale image can store discrete pixels with conventional brightness intensities between 0 and 255.
  • each channel is made of 16-bit grayscale images.
  • the periodogram is an estimate of the spectral density of a signal.
  • the term "spectral plot" refers to a smoothed version of the periodogram. Smoothing is performed to reduce the effect of measurement noise.
  • Convolution unit 7426 convolutes the Red (R) and Blue (B) color channel spectral plots by subtracting the spectral plot for the polarized optical electromagnetic signal from the non-polarized optical electromagnetic signal for each color to generate Red (R) and Blue (B) normalized, composite color channel spectral plots and subtracting the normalized, composite Blue (B) channel spectral plot from the normalized, composite Red (R) channel spectral plot thereby resulting in generation of a spectral signature for the blood plasma samples.
  • the spectral signature is analyzed for at least one of number of crests and troughs, amplitude, shape of peaks, intermediate structures and patterns. In certain such embodiments, the spectral signature is analysed for material composition, identification, purity and the like.
  • the system configuration discussed in conjunction with FIGS. 73 and 74, implement one or more processes facilitating estimation of blood plasma type and properties (or characteristics) thereof to create a unique spectral signature.
  • FIG. 75 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 73 and 74 thereby facilitating estimation of blood plasma type and properties (or characteristics) thereof and creation of a unique spectral signature.
  • the process 7500 starts at stage 7502 and proceeds to stage 7504, wherein the process 7500 comprises the phase of convolution of data associated with a first set of images of a blood plasma sample captured by illuminating the sample with a white light (or unangled white light.) Noticeable here is the fact that the data associated with the first set of images of the blood plasma sample illuminated with the white light (or unangled white light) may comprise one or more combinations of reflected and re-emitted angled and unangled white light.
  • the process 7500 comprises the phase of convolution of data associated with a second set of images of the blood plasma sample captured by illuminating the sample with an angled white light.
  • the data associated with the second set of images of the blood plasma sample illuminated with the angled white light may comprise one or more combinations of reflected and re-emitted angled white light.
  • the process 7500 comprises the phase of comparison of extrema (i.e. maxima and minima) (or extreme) positions of at least a pair of unique convolutions generated by convolution of data from the first set of images and second set of images.
  • the process 7500 comprises the phase of determination of a distance between minimum and maximum (or extremum) intensity positions in convoluted Red (R) minus Blue (B) spectral plots from the pair of unique convolutions generated by convolution of data from the first set of images and second set of images to generate a numerical (or quantitative) blood plasma type.
  • the process 7500 ends at stage 7512.
  • the phase of comparison of extrema (i.e. maxima and minima) (or extreme) positions of at least a pair of unique convolutions comprises implementation of one or more sub- phases.
  • the one or more sub-phases include comparison of a first component Red (R) minus Blue (B) of unangled white light (or W) minus angled white light (or polarized white light or P) (i.e. (R - B) (W - P)) versus a second component Red (R) minus Blue (B) of unangled white light (or W) (i.e. (R - B) W).
  • the two unique convolutions in unangled white light and angled (or polarized) white light further include a White Red component (WR), a White Blue component (WB), a reflected and / or re-emitted Polarized Blue component (PB) and a reflected and / or re-emitted Polarized Red component (PR).
  • the two unique convolutions are based on a numerical value difference correlating to medical standards.
  • the step of comparing extreme positions of at least two unique convolutions includes comparing a component (R - B) (W - P) for the reflected and / or re-emitted polarized light, and a component (R - B) W for the white light.
  • the step of comparing extreme positions of at least two unique convolutions includes a spectral convolution scheme, wherein multiple combinations of subtraction of Blue (B) spectrum from Red (R), in white light and polarized white light are determined, wherein the spectral interval is expressed in a wavelength scale interval of 100 nanometers to 300 nanometers.
  • the investigation of viral infection performed over a sample set taken from 40 pregnant women is disclosed.
  • the sample set is classified by blood test in two groups, namely EBV group (32 cases, M, GM) and CMV group (8 cases M, GM). Further, each group is separated into two categories, namely positive (virus present, 16 EBV and 4 CMV) and negative (virus absent, 16 EBV and 4 CMV) respectively.
  • EBV group 32 cases, M, GM
  • CMV group 8 cases M, GM
  • each group is separated into two categories, namely positive (virus present, 16 EBV and 4 CMV) and negative (virus absent, 16 EBV and 4 CMV) respectively.
  • the sample set is subjected to diagnosis using standard Enzyme Immunoassay Method (or ELISA).
  • FIGS. 76A and 76B depict a dual pair of typical digital images of samples, tested positive and negative for EBV and CMV, captured with diffuse white light (W) and reflected polarized light (P), in that order.
  • W diffuse white light
  • P reflected polarized light
  • FIG. 76A a first pair of the dual pair of digital photography images of blood plasma samples of pregnant women captured with diffuse white light and reflected polarized tested positive for presence of EBV.
  • both the positively tested blood plasma samples have been referred to as "POSITIVE 00 30MG”.
  • FIG. 76B a second pair of the dual pair of digital photography images of blood plasma samples of pregnant women captured with diffuse white light and reflected polarized tested negative for presence of EBV are shown in FIG. 76B.
  • both the negatively tested blood plasma samples have been referred to as "NEGATIVE 02 733MG”.
  • FIGS. 76A and 76B Observation of images in FIGS. 76A and 76B by naked eye would probably testify that there are no differences between them. However, using Computer Assisted Analysis (CAA) based on pixel by pixel count and Spectral Convolution Algorithm (SCA), significant differences are found, the final result of which is illustrated in conjunction with FIGS. 77A-B, 78A-B, 79A-B and 80A-B, respectively.
  • CAA Computer Assisted Analysis
  • SCA Spectral Convolution Algorithm
  • a limited number of typical cases of EBV are selected and presented for purposes of illustration. Specifically, four typical cases of EBV, namely two IgM and two IgG, to illustrate the difference between positive and negative of same cases (i.e. IgM or IgG) and similarity of spectral data.
  • IgG or Immunoglobulin G refers to a monomeric immunoglobulin built of two heavy chains ⁇ and two light chains. Each IgG has two antigen binding sites. It is the most abundant immunoglobulin and is approximately equally distributed in blood and in tissue liquids, constituting 75% of serum immunoglobulins in humans. IgG molecules are synthesized and secreted by plasma B cells.
  • IgM immunoglobulin M
  • B cells The term “Immunoglobulin M” refers to a basic antibody that is present on B cells. It is the primary antibody against A and B antigens on red blood cells. IgM is by far the physically largest antibody in the human circulatory system. It is the first antibody to appear in response to initial exposure to antigen.
  • CAA based on pixel by pixel count and SCA is implemented taking into consideration only four typical cases of EBV, namely two IgM and two IgG, thereby facilitating illustration of difference between positive and negative of same cases (i.e. IgM or IgG) and similarity of spectral data.
  • a two (or 2 D)-dimensional coordinate system including a horizontal X-axis and a vertical Y-axis is selected.
  • the horizontal X-axis represents the wavelength difference in nanometers whereas the vertical Y-axis represents the intensity in suitable units.
  • FIGS. 77A and 77B depict a first pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a first set of two patients subjected to a first test case for confirmation of EBV, namely "Case I: EBV-lgM", designed and implemented in accordance with certain embodiments of the invention.
  • the 2D coordinate system is in essence a Difference Versus Intensity plot (or Dl plot) obtained on plotting a plurality of Dl ordered pairs.
  • Each of the plurality of ordered pairs includes a Wavelength Difference value and a corresponding Intensity value.
  • the plurality of ordered pairs are obtained on processing the digital images of blood plasma samples, captured using diffuse white light and reflected polarized light, using the OMF method.
  • the OMF method implements the SCA and CAA to analyze the processed digital images of the blood plasma samples.
  • the blood plasma samples are collected from two different patients subjected to test for presence or absence of EBV-lgM.
  • a first Dl plot of the first pair of Dl plots possess the following specifications and associated test information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X-axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.15 to a maximum of equal to +0.15; test is analysis for confirmation of presence or absence of EBV in blood plasma sample; patient information is a first patient of the first set is a pregnant woman bearing optional or exemplary patient number is patient no.
  • test input sample is blood plasma of the patient; test case is EBV-lgM; test output is positive; operation is OMF method; number of intensity peaks (or extrema or maxima and minima) is 4; identifiers for the 4 intensity peaks are first 7702A, second 7704A, third 7706A and fourth 7708A respectively; values for Wavelength Difference / Intensity associated with the first 7702A, second 7704A, third 7706A and fourth 7708A intensity peaks are 126.6 nm / 0.113, 129.7 nm / -0.095, 160.8 nm / -0.041 , 162.1 nm / 0.041 in that order.
  • a second Dl plot of the first pair of Dl plots possess the following specifications and associated test information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X-axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.2 to a maximum of equal to +0.15; test is analysis for confirmation of presence or absence of EBV in blood plasma sample; patient information is a second patient of the first set is a pregnant woman bearing optional or exemplary patient number is patient no.
  • test input sample is blood plasma of the patient; test case is EBV-lgM; test output is negative; number of intensity peaks (or extrema or maxima and minima) is 3; identifiers for the 3 intensity peaks are fifth 771 OA, sixth 7712A and seventh 7714 A respectively; values for Wavelength Difference / Intensity associated with the fifth, sixth and seventh intensity peaks are 122.0 nm / 0.107, 163.4 nm / -0.151 , 187.8 nm / 0.084 in that order.
  • FIGS. 78A and 78B depict a second pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a second set of two different patients subjected to a second test case for confirmation of EBV, namely "Case II: EBV-lgM", designed and implemented in accordance with certain embodiments of the invention.
  • a third Dl plot of the second pair of Dl plots possess the following specifications and associated test information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X-axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.06 to a maximum of equal to +0.12; test is analysis for confirmation of presence or absence of EBV in blood plasma sample; patient information is a first patient of the second set is a pregnant woman bearing optional or exemplary patient number is patient no.
  • test input sample is blood plasma of the patient; test case is EBV-lgM; test output is positive; operation is OMF method; number of intensity peaks (or extrema or maxima and minima) is 4; identifiers for the 4 intensity peaks are first 7802A, second 7804A, third 7806A and fourth 7808A respectively; values for Wavelength Difference / Intensity associated with the first 7802A, second 7804A, third 7806A and fourth 7808A intensity peaks are 126.6 nm / 0.110, 132.3 nm / -0.060, 157.8 nm / 0.023, 160.2 nm / -0.026 in that order.
  • a fourth Dl plot of the second pair of Dl plots possess the following specifications and associated test information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X-axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.25 to a maximum of equal to +0.2; test is analysis for confirmation of presence or absence of EBV in blood plasma sample; patient information is a second patient of the second set is a pregnant woman bearing optional or exemplary patient number is patient no.
  • ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value)
  • horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a
  • test input sample is blood plasma of the patient; test case is EBV-lgM; test output is negative; number of intensity peaks (or extrema or maxima and minima) is 3; identifiers for the 3 intensity peaks are fifth 781 OA, sixth 7812A and seventh 7814A respectively; values for Wavelength Difference / Intensity associated with the fifth 781 OA, sixth 7812A and seventh 7814A intensity peaks are 122.2 nm / 0.132, 169.3 nm / -0.225, 187.8 nm / 0.169 in that order.
  • FIGS. 79A and 79B depict a third pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a third set of two different patients subjected to a third test case for confirmation of EBV, namely "Case III: EBV-lgG", designed and implemented in accordance with certain embodiments of the invention.
  • a fifth Dl plot of the third pair of Dl plots possess the following specifications and associated test information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X-axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.15 to a maximum of equal to +0.15; test is analysis for confirmation of presence or absence of EBV in blood plasma sample; patient information is a first patient of the third set is a pregnant woman bearing optional or exemplary patient number is patient no.
  • test input sample is blood plasma of the patient; test case is EBV-lgG; test output is positive; operation is OMF method; number of intensity peaks (or extrema or maxima and minima) is 4; identifiers for the 4 intensity peaks are first 7902A, second 7904A, third 7906A and fourth 7908A respectively; values for Wavelength Difference / Intensity associated with the first 7902A, second 7904A, third 7906A and fourth 7908A intensity peaks are 121 .7 nm / 0.120, 151 .3 nm / -0.059, 166.3 nm / -0.117, 168.4 nm / 0.121 in that order.
  • a sixth Dl plot of the third pair of Dl plots possess the following specifications and associated test information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X-axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.25 to a maximum of equal to +0.15; test is analysis for confirmation of presence or absence of EBV in blood plasma sample; patient information is a second patient of the third set is a pregnant woman bearing optional or exemplary patient number is patient no.
  • ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value)
  • horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to
  • test input sample is blood plasma of the patient; test case is EBV-lgG; test output is negative; number of intensity peaks (or extrema or maxima and minima) is 3; identifiers for the 3 intensity peaks are fifth 791 OA, sixth 7912A and seventh 7914A respectively; values for Wavelength Difference / Intensity associated with the fifth 791 OA, sixth 7912A and seventh 7914A intensity peaks are 122.0 nm / 0.1 15, 169.3 nm / -0.203, 187.8 nm / 0.1 14 in that order.
  • FIGS. 80A and 80B depict a fourth pair of plots of typical spectral data obtained on implementation of the OMF method for processing digital images of unique samples from a fourth set of two different patients subjected to a fourth test case for confirmation of EBV, namely "Case IV: EBV-lgG", designed and implemented in accordance with certain embodiments of the invention.
  • a seventh Dl plot of the fourth pair of Dl plots possess the following specifications and associated test information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X-axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.15 to a maximum of equal to +0.15; test is analysis for confirmation of presence or absence of EBV in blood plasma sample; patient information is a first patient of the fourth set is a pregnant woman bearing optional or exemplary patient number is patient no.
  • test input sample is blood plasma of the patient; test case is EBV-lgG; test output is positive; operation is OMF method; number of intensity peaks (or extrema or maxima and minima) is 4; identifiers for the 4 intensity peaks are first 8002A, second 8004A, third 8006A and fourth 8008A respectively; values for Wavelength Difference / Intensity associated with the first 8002A, second 8004A, third 8006A and fourth 8008A intensity peaks are 123.6 nm / 0.098, 155.7 nm / -0.061 , 168.4 nm / -0.106, 172.2 nm / 0.087 in that order.
  • a eighth Dl plot of the fourth pair of Dl plots possess the following specifications and associated test information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X-axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.3 to a maximum of equal to +0.25; test is analysis for confirmation of presence or absence of EBV in blood plasma sample; patient information is a second patient of the fourth set is a pregnant woman bearing optional or exemplary patient number is patient no.
  • ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value)
  • horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a
  • test input sample is blood plasma of the patient; test case is EBV-lgG; test output is negative; number of intensity peaks (or extrema or maxima and minima) is 3; identifiers for the 3 intensity peaks are fifth, sixth and seventh respectively; values for Wavelength Difference / Intensity associated with the fifth, sixth and seventh intensity peaks are 120.5 nm / 0.123, 176.1 nm / -0.175, 200.3 nm / 0.203 in that order.
  • FIGS. 77A-B, 78A-B, 79A-B and 80A-B show that the 40 samples examined for presence of EBV or CMV the following distinctive features are observed in the FIGS. 77A-B, 78A-B, 79A-B and 80A-B: number of peaks, position of peaks, distribution of peaks (up and down), and individual peak intensity. Regarding all the aforementioned features it is seen that it is possible to group the FIGS. 77A-B, 78A-B, 79A-B and 80A-B based on the antibody type (i.e. IgG / IgM) and the test results (i.e. positive/negative). The intensities as well as wavelength differences for IgM antibodies differ from those for IgG antibodies.
  • the antibody type i.e. IgG / IgM
  • test results i.e. positive/negative
  • spectral data of all 40 cases presented in the FIGS. 77A-B, 78A-B, 79A-B and 80A-B display information regarding the difference between normal (i.e. negative) and virus infected (i.e. positive) blood plasma samples.
  • OMF spectral plots or DI-OMF
  • this algorithm still needs to be refined in order to more clearly distinguish which type of virus infection is present.
  • OMF method could be used as an adjunct method in virus detection since it yields good results in quick identification of virus infection presence. It can save time and money when used in parallel with expensive biochemical analysis.
  • FIG. 81 is a block diagrammatic view of a system facilitating implementation of an Opto-Magnetic process based on light-matter interaction using digital imaging for Papanicolau Test Analysis of samples, designed and implemented in accordance with certain embodiments of the invention.
  • System 8100 is in essence a Papanicolau Test Analyzer (or PTA).
  • the PTA 8100 includes an illumination subsystem 8102, an imaging (or sensor) subsystem 8104 and a host computing subsystem 8106.
  • PTA 8100 by virtue of its design and implementation, facilitates execution of an Opto-Magnetic method based on interaction between electromagnetic radiation and matter, for instance light-matter interaction, using digital imaging for analysis of samples subjected to Papanicolau Test.
  • the Opto-Magnetic process employs apparatuses for generation of unique spectral signatures from digitally captured images of samples thereby facilitating analysis of the samples subjected to Papanicolau Test based on Opto-Magnetic properties of light-blood plasma interaction.
  • Illumination subsystem 8102 may be one or more electromagnetic radiation sources.
  • the Illumination subsystem 8102 may be a set of Light Emitting Diodes (LEDs).
  • Illumination subsystem 8102 may be adapted to emit polarized and unpolarized electromagnetic signals. The polarized electromagnetic signal is angled white light and unpolarized electromagnetic signal is non-angled white light.
  • the illumination subsystem 8102 may be coupled to the sensor subsystem 8104.
  • the sensor subsystem 804 may in essence be a device that converts optical images (or optical signals) to electric signals.
  • the sensor subsystem 8104 captures continuous digital images of blood plasma samples.
  • the sensor subsystem 8104 captures continuous digital images of the blood plasma samples illuminated with white light both, non-angled and angled.
  • the sensor subsystem 8104 may be anyone selected from a group consisting of a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor, Charged Coupled Device (CCD) image sensor, and the like.
  • CMOS Complementary Metal-Oxide-Semiconductor
  • CCD Charged Coupled Device
  • the sensor subsystem 8104 may be coupled to the host computing subsystem 8106.
  • the sensor subsystem 8104 may be selected on the basis of the following specifications: color is color or monochrome; optical format; horizontal pixels X vertical pixels; pixel size; one or more performance parameters, such as maximum frame rate, data rate, maximum power dissipation, quantum efficiency, dynamic range and supply voltage; output; one or more features, such as integrated Analog-to-Digital Converter (ADC) and microlenses; and environment, such as operating temperature.
  • ADC Analog-to-Digital Converter
  • FIG. 82 is an exploded diagrammatic representation of the host computing subsystem, of the Fig. 81 , comprising the Opto-Magnetic Fingerprint (or OMF) Generator module designed and implemented in accordance with at least some embodiments.
  • OMF Opto-Magnetic Fingerprint
  • the host computing subsystem 8200 may comprise a processing unit 8202, a memory unit 8204 and an Input / Output (or I / O) unit 206 respectively.
  • the host computing subsystem 8200 by virtue of its design and implementation, performs overall management of blood plasma samples.
  • the processing unit 8202 may comprise an Arithmetic Logic Unit (or ALU) 8208, a Control Unit (or CU) 8210 and a Register Unit (or RU) 8212.
  • ALU Arithmetic Logic Unit
  • CU Control Unit
  • RU Register Unit
  • the memory unit 8204 comprises a test analysis module 8214.
  • the test analysis module for analysis of samples subjected to Papanicolau Test via generation of unique spectral signatures from the digitally captured images of the samples and methods thereof are disclosed, in accordance with the principles of the invention.
  • the test analysis module utilizes the continuously captured digital images of the samples illuminated with white light both, non-angled and angled. More specifically, the blood plasma virus detection module takes into consideration the digital images in Red (R), Green (G) and Blue (B) (or RGB) system for purposes of analysis.
  • the test analysis module 8214 includes a Fourier transform sub- module 8216, a spectral analyzer sub-module 8218 and an Opto-Magnetic Fingerprint Generator (or OMFG) sub-module 8220, respectively.
  • OMFG Opto-Magnetic Fingerprint Generator
  • the Fourier transform sub-module 8216 is in essence a Discrete-Time Fourier Transform (or DTFT).
  • DTFT refers to one of the specific forms of Fourier analysis. As such, it transforms one function into another, which is called the frequency domain representation, or simply the "DTFT", of the original function, which is often a function in the time-domain. But, the DTFT requires an input function that is discrete. Such inputs are often created by sampling a continuous function, like a person's voice.
  • the DTFT frequency-domain representation is always a periodic function. Since one period of the function contains all of the unique information, it is sometimes convenient to say that the DTFT is a transform to a "finite" frequency-domain (the length of one period), rather than to the entire real line.
  • DTFT 8216 converts time-domain digital signals into corresponding frequency-domain digital signals.
  • DTFT 8216 is coupled to the spectrum analyzer sub-module 8218.
  • the term "spectrum analyzer” refers to a device used to examine the spectral composition of some electrical, acoustic, or optical waveform. It may also measure the power spectrum.
  • spectrum analyzers there are three types of spectrum analyzers, such as analog, digital and real-time spectrum analyzers. Firstly, an analog spectrum analyzer uses either a variable band-pass filter whose mid- frequency is automatically tuned (i.e. shifted, swept) through the range of frequencies of the spectrum to be measured or a superheterodyne receiver, wherein the local oscillator is swept through a range of frequencies.
  • a digital spectrum analyzer computes the Discrete Fourier transform (or DFT), a mathematical process that transforms a waveform into the components of its frequency spectrum.
  • DFT Discrete Fourier transform
  • some spectrum analyzers such as "real-time spectrum analyzers" use a hybrid technique where the incoming signal is first down-converted to a lower frequency using superheterodyne techniques and then analyzed using fast Fourier transformation (FFT) techniques.
  • FFT fast Fourier transformation
  • the spectrum (or spectral) analyzer sub-module for analysis of digitally captured images of samples thereby facilitating analysis of the samples subjected to Papanicolau Test is disclosed.
  • the spectrum (or spectral) analyzer sub-module in order to analyze the samples takes into consideration digital images of the samples in Red (R), Green (G) and Blue (B) (or RGB) system.
  • basic pixel data in Red (R) and Blue (B) channels for both white diffuse light (or W) and reflected polarized light (or P) is selected.
  • the algorithm for data analysis is based on chromaticity diagram called "Maxwell's triangle" and spectral convolution.
  • the digital images in Red (R), Green (G) and Blue (B) (or RGB) system are taken into consideration for purposes of spectral analysis.
  • basic pixel data in Red (R) and Blue (B) channels for white diffuse light (or W) and reflected polarized white light (or P) is selected.
  • the algorithm for data analysis is based on chromaticity diagram called "Maxwell's triangle" and spectral convolution operation, in accordance with a ratio of (R - B) & (W - P).
  • R Red
  • B Blue
  • W White light
  • P reflected Polarized light
  • method and algorithm for creating unique spectral fingerprint are based on the convolution of RGB color channel spectral plots generated from digital images that capture single and multi-wavelength light-matter interaction for different paramagnetic materials, such as Al, Mn and Ti, diamagnetic materials, such as Cu, C and Zn, alloys, such asPbl-xMnxTe, Biomolecules and biological tissues as paramagnetic / diamagnetic materials, such as skin, biological water, amniotic fluid, blood plasma and the like.
  • paramagnetic materials such as Al, Mn and Ti
  • diamagnetic materials such as Cu, C and Zn
  • alloys such asPbl-xMnxTe
  • Biomolecules and biological tissues as paramagnetic / diamagnetic materials, such as skin, biological water, amniotic fluid, blood plasma and the like.
  • incident white light can give different information about properties of thin layer of matter, such as blood plasma sample surface, depending on the angle of light incidence.
  • the reflected white light is then composed of electrical and magnetic components, whereas diffuse incident light that is inclined under certain angle will produce reflected light which contains only electrical component of light.
  • the spectrum analyzer sub-module 8218 may be coupled to the OMFG sub- module 8220.
  • OMFG sub-module 8220 includes a color histogram generator unit 8222, a spectral plot generator unit 8224 and a convolution unit 8226.
  • OMFG sub-module 8214 by virtue of its design and implementation, facilitates generation of unique spectral signatures from digitally captured images of Pap test samples. Specifically, the generated spectral signatures of Pap test samples facilitate detection of cancer based on Opto-Magnetic properties of light-blood plasma interaction.
  • Color histogram generator unit 8222 by virtue of its design, generates a normalized Red (R) and Blue (B) color channel histogram for each of the one or more images of the blood plasma samples.
  • color histogram refers to is a representation of the distribution of colors in an image, derived by counting the number of pixels of each of given set of color ranges in a typically two-dimensional (2D) or three-dimensional (3D) color space.
  • a histogram is a standard statistical description of a distribution in terms of occurrence frequencies of different event classes; for color, the event classes are regions in color space.
  • An image histogram of scalar pixel values is more commonly used in image processing than is a color histogram.
  • image histogram refers to a type of histogram which acts as a graphical representation of the tonal distribution in a digital image. It plots the number of pixels for each tonal value. By looking at the histogram for a specific image a viewer is able to judge the entire tonal distribution at a glance.
  • color histograms are flexible constructs that can be built from images in various color spaces, whether RGB, rg chromaticity or any other color space of any dimension.
  • a histogram of an image is produced first by discretization of the colors in the image into a number of bins, and counting the number of image pixels in each bin.
  • the color histogram generator unit 8222 may be coupled to the spectral plot generator unit 8224.
  • Spectral plot generator unit 224 generates Red (R) and Blue (B) color channel spectral plots by correlating the normalized Red (R) and Blue (B) color channel histograms to a wavelength scale.
  • a unit scale on the spectral signature is a difference of wavelength.
  • color digital images are made of pixels and, in turn, pixels are made of combinations of primary colors.
  • channel refers to the grayscale image of the same size as a color image, made of just one of these primary colors.
  • an image from a standard digital camera will have a red, green and blue channel.
  • a grayscale image has just one channel.
  • an RGB image has three channels, namely Red (R), Green (G) and Blue (B).
  • R Red
  • G Green
  • B Blue
  • the RGB image is 24-bit then each channel has 8 bits, for R, G and B.
  • the image is composed of three grayscale images, where each grayscale image can store discrete pixels with conventional brightness intensities between 0 and 255.
  • each channel is made of 16-bit grayscale images.
  • the periodogram is an estimate of the spectral density of a signal.
  • the term "spectral plot" refers to a smoothed version of the periodogram. Smoothing is performed to reduce the effect of measurement noise.
  • Convolution unit 8226 convolutes the Red (R) and Blue (B) color channel spectral plots by subtracting the spectral plot for the polarized optical electromagnetic signal from the non-polarized optical electromagnetic signal for each color to generate Red (R) and Blue (B) normalized, composite color channel spectral plots and subtracting the normalized, composite Blue (B) channel spectral plot from the normalized, composite Red (R) channel spectral plot thereby resulting in generation of a spectral signature for the Pap test samples.
  • the spectral signature is analyzed for at least one of number of crests and troughs, amplitude, shape of peaks, intermediate structures and patterns. In certain such embodiments, the spectral signature is analysed for material composition, identification, purity and the like.
  • FIG. 83 depicts a flow diagram delineating at least one process implemented by the system configuration of FIGS. 81 and 82 thereby facilitating estimation of Pap test sample type and properties (or characteristics) thereof and creation of a unique spectral signature.
  • the process 8300 starts at stage 8302 and proceeds to stage 8304, wherein the process 8300 comprises the phase of convolution of data associated with a first set of images of a Pap test sample captured by illuminating the sample with a white light (or unangled white light.) Noticeable here is the fact that the data associated with the first set of images of the Pap test sample illuminated with the white light (or unangled white light) may comprise one or more combinations of reflected and re-emitted angled and unangled white light.
  • the process 8300 comprises the phase of convolution of data associated with a second set of images of the Pap test sample captured by illuminating the sample with an angled white light.
  • the data associated with the second set of images of the Pap test sample illuminated with the angled white light may comprise one or more combinations of reflected and re-emitted angled white light.
  • the process 8300 comprises the phase of comparison of extrema (i.e. maxima and minima) (or extreme) positions of at least a pair of unique convolutions generated by convolution of data from the first set of images and second set of images.
  • extrema i.e. maxima and minima
  • extreme positions of at least a pair of unique convolutions generated by convolution of data from the first set of images and second set of images.
  • the process 8300 comprises the phase of determination of a distance between minimum and maximum (or extremum) intensity positions in convoluted Red (R) minus Blue (B) spectral plots from the pair of unique convolutions generated by convolution of data from the first set of images and second set of images to generate a numerical (or quantitative) Pap test sample type.
  • the process 8300 ends at stage 8312.
  • the phase of comparison of extrema (i.e. maxima and minima) (or extreme) positions of at least a pair of unique convolutions comprises implementation of one or more sub- phases.
  • the one or more sub-phases include comparison of a first component Red (R) minus Blue (B) of unangled white light (or W) minus angled white light (or polarized white light or P) (i.e. (R - B) (W - P)) versus a second component Red (R) minus Blue (B) of unangled white light (or W) (i.e. (R - B) W).
  • the two unique convolutions in unangled white light and angled (or polarized) white light further include a White Red component (WR), a White Blue component (WB), a reflected and / or re-emitted Polarized Blue component (PB) and a reflected and / or re-emitted Polarized Red component (PR).
  • the two unique convolutions are based on a numerical value difference correlating to medical standards.
  • the exploded diagrammatic representation in FIG. 74 of the host computing subsystem, of the Fig. 71 may comprise the Opto-Magnetic Fingerprint (or OMF) Generator sub-module designed and implemented in accordance with at least some embodiments.
  • OMF Opto-Magnetic Fingerprint
  • the step of comparing extreme positions of at least two unique convolutions includes comparing a component (R - B) (W - P) for the reflected and / or re-emitted polarized light, and a component (R - B) W for the white light.
  • the step of comparing extreme positions of at least two unique convolutions includes a spectral convolution scheme, wherein multiple combinations of subtraction of Blue (B) spectrum from Red (R), in white light and polarized white light are determined, wherein the spectral interval is expressed in a wavelength scale interval of 100 nanometers to 300 nanometers.
  • the investigation of Pap test performed, as adjunct to yearly screening, over a sample set taken from 40 women is disclosed.
  • the 40 samples are prepared for standard Pap test and examined as double-blind experiment using digital imaging software that analyzes the difference between reflected diffuse white light and reflected polarized light (Opto- Magnetic Fingerprint-OMF) in order to detect normal, dysplastic and cancerous cells.
  • Opto- Magnetic Fingerprint-OMF digital imaging software that analyzes the difference between reflected diffuse white light and reflected polarized light
  • the samples were prepared according to standard fixation and staining procedures used for Pap smear tests during regular colposcopic examination.
  • Opto-magnetic images of samples are analyzed using a digital camera customized for capturing OMF pictures (or DI-OMF) and light-mater interaction analysis software (DI-OMF), which guides the diagnostic decision to more refined distinction between normal smear and the one containing either dysplastic or cancerous cells.
  • DI-OMF OMF pictures
  • DI-OMF light-mater interaction analysis software
  • double-blind experiment or double-blind trials refers to an especially stringent way of conducting an experiment, usually on human subjects, in an attempt to eliminate subjective bias on the part of both experimental subjects and the experimenters. In most cases, double-blind experiments are held to achieve a higher standard of scientific rigor. In a double-blind experiment, neither the individuals nor the researchers know who belongs to the control group and the experimental group. Only after all the data have been recorded (and in some cases, analyzed) do the researchers learn which individuals are which. Performing an experiment in double-blind fashion is a way to lessen the influence of the prejudices and unintentional physical cues on the results (the placebo effect, observer bias, and experimenter's bias). Random assignment of the subject to the experimental or control group is a critical part of double- blind research design. The key that identifies the subjects and which group they belonged to is kept by a third party and not given to the researchers until the study is over.
  • the DI-OMF diagrams are separated into five groups. Subsequent to completion of DI-OMF analysis, randomized samples codes were removed and a comparative analysis of results of DI-OMF vis-a-vis Pap test is performed. Analysis of the results of comparison show that 40 slides were categorized by standard Pap test examination into five groups, namely Group I (or normal tissue state) 7 cases, Group II (or non-typical inflammation) 8 cases, Group III (or dysplasia) 17 cases, Group IV (or carcinoma in situ) 5 cases and Group V (or suspicion to carcinoma) 3 cases.
  • Group I or normal tissue state
  • Group II or non-typical inflammation
  • Group III or dysplasia
  • Group IV or carcinoma in situ
  • Group V or suspicion to carcinoma
  • Table 4 exhibits a tabular representation in connection with the comparative analysis of results of Pap test vis-a-vis DI-OMF and matching results thereof.
  • one or more typical digital images of Pap smear slide samples categorized as Group I, captured using diffuse white light and reflected polarized light are selected for purposes of observation and analysis.
  • FIGS. 84A-B, 85A-B and 86A-B depict a triple pair of typical digital images of samples (or Pap smear slides), categorized as Group I (or normal tissue state), captured with diffuse white light (W) and reflected polarized light (P), in that order.
  • Group I or normal tissue state
  • W diffuse white light
  • P reflected polarized light
  • the sample categorized as Group I is collected from a first patient herein referred to as Group I Patient 1 .
  • the digital photography images of the sample captured using the diffuse white light and reflected polarized light have been labeled as "LEFT" and "RIGHT", in that order.
  • group I or normal tissue state
  • the sample categorized as Group I is collected from a second patient herein referred to as Group I Patient 2.
  • the digital photography images of the sample captured using the diffuse white light and reflected polarized light have been labeled as "LEFT” and "RIGHT", in that order.
  • group I or normal tissue state
  • the sample categorized as Group I is collected from a third patient herein referred to as Group I Patient 3.
  • the digital photography images of the sample captured using the diffuse white light and reflected polarized light have been labeled as "LEFT” and "RIGHT", in that order.
  • a limited number of typical cases comprising samples (or Pap smear slides) categorized into one or more groups based on states of samples, such as "Group I (or normal tissue state),” “Group II (or non-typical inflammation),” “Group III (or dysplasia),” “Group IV (or carcinoma in situ),” and “Group V (or suspicion to carcinoma)", are selected and presented for purposes of illustration.
  • Group I namely one "Group I Patient 1 ,” one "Group I Patient 2,” and one “Group I Patient 3", and one case from each of the Groups II, III, IV and V, namely "Group II Patient 17,” “Group III Patient 16,” “Group IV Patient 4,” and “Group V Patient 7", are selected and presented for purposes of illustration.
  • CAA based on pixel by pixel count and SCA is implemented taking into consideration only three typical cases of Group I, namely one "Group I Patient 1 ,” one "Group I Patient 2,” and one “Group I Patient 3", and one case from each of the Groups II, III, IV and V, namely "Group II Patient 17,” “Group III Patient 16,” “Group IV Patient 4,” and “Group V Patient 7", thereby facilitating illustration of characteristics of spectral data thereof.
  • a two (or 2 D)-dimensional coordinate system including a horizontal X-axis and a vertical Y-axis is selected for purposes of illustration of the spectral data obtained on implementation of the CAA and SCA.
  • the horizontal X-axis represents the wavelength difference in nanometers whereas the vertical Y-axis represents the intensity in suitable units.
  • the 2D coordinate system exhibits the comparative analysis of wavelength difference versus intensity for given samples collected from given patients and subjected to tests for presence or absence of normal, dysplastic and cancerous cells, wherein the wavelength difference is the independent variable and the intensity is the dependent variable.
  • FIG. 84C depicts a plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of FIGS. 84A-B of the given, selected first sample (or Pap smear slide) categorized as Group I (or normal tissue state), in accordance with certain embodiments of the invention.
  • the 2D coordinate system is in essence a Wavelength Difference Versus Intensity plot (or Dl plot or OMF diagram) obtained on plotting a plurality of Dl ordered pairs.
  • Each of the plurality of ordered pairs includes a Wavelength Difference value and a corresponding Intensity value.
  • the plurality of ordered pairs are obtained on processing the digital image of the first sample, captured using diffuse white light and reflected polarized light, using the OMF method.
  • the OMF method implements the SCA and CAA to analyze the processed digital image of the sample.
  • a first Dl plot possesses the following specifications and associated analytical information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X- axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.025 to a maximum of equal to +0.015; analytical information is analysis of the first Dl plot (or OMF Diagram) of the sample; patient information is a given, selected first patient of the Group I (or normal tissue state) or Group I Patient 1 ; test input sample is
  • 4A-B of the given, selected first sample (or Pap smear slide) categorized as Group I (or normal tissue state); number of intensity peaks (or extrema or maxima and minima) is 3; number of peaks with positive intensity values is 2; number of peaks with negative intensity value is 1 ; identifiers for the 3 intensity peaks are first 8402A, second 8404A and third 8408A respectively; values for Wavelength Difference / Intensity associated with the first 8402A, second 8404A and third 8406A intensity peaks are 105.5 nm / 0.095 Intensity (arb units), 1 13.7 nm / -0.022 arb and 1 19.2 nm / 0.012 arb in that order.
  • FIG. 85C depicts a plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of FIGS. 85A-B of the given, selected second sample (or Pap smear slide) categorized as Group I (or normal tissue state), in accordance with certain embodiments of the invention.
  • a second Dl plot possess the following specifications and associated analytical information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X- axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.025 to a maximum of equal to +0.015; analytical information is analysis of the second Dl plot (or OMF Diagram) of the digital photography image of the sample; patient information is the given, selected second patient of the Group I (or normal tissue state) or Group I Patient 2; test input sample is the Pap smear slide categorized as the Group I (or normal tissue state) of the patient referred to as Group I Patient 2; operation is implementation of OMF method on digital images of FIGS.
  • ordered (or Dl) pair is (Wave
  • FIG. 86C depicts a plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of FIGS. 86A-B of the given, selected third sample (or Pap smear slide) categorized as Group I (or normal tissue state), in accordance with certain embodiments of the invention.
  • Group I or normal tissue state
  • a third Dl plot possess the following specifications and associated analytical information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X- axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.025 to a maximum of equal to +0.015; analytical information is analysis of the third Dl plot (or OMF Diagram) of the digital photography image of the sample; patient information is the given, selected third patient of the Group I (or normal tissue state) or Group I Patient 3; test input sample is the Pap smear slide categorized as the Group I (or normal tissue state) of the patient referred to as Group I Patient 3; operation is implementation of OMF method on digital images of FIGS.
  • ordered (or Dl) pair is (Wave
  • 86A-B of the given, selected third sample categorized as Group I (or normal tissue state); number of intensity peaks (or extrema or maxima and minima) is 3; number of intensity peaks (or extrema or maxima and minima) is 3; number of peaks with positive intensity values is 2; number of peaks with negative intensity value is 1 ; identifiers for the 3 intensity peaks are first 8602A, second 8604A and third 8606A respectively; values for Wavelength Difference / Intensity associated with the first, second and third intensity peaks are 109.0 nm / 0.0098 arb, 114.0 nm / -0.024 arb and 117.9 nm / 0.0102 arb in that order.
  • FIGS. 84A-B, 85A-B and 86A-B are different, their OMF diagrams appear almost identical.
  • FIGS. 84C, 85C and 86C three peaks are seen, wherein a pair of the peaks possesses very similar positive intensity values (i.e. 108 nm and 1 18 nm) and one with a larger negative intensity value (i.e. 1 13 nm).
  • These values are valid for spectral convolution field. They are symmetrical and indicate normal tissue state. Reason for this is same Pap group, which is in this case normal.
  • one or more typical cases comprising samples (or Pap smear slides) categorized as group II (or non-typical inflammation) are selected and presented for purposes of illustration. Specifically, one typical case including a sample categorized as group II (or non-typical inflammation) is taken into consideration and presented for purposes of illustration.
  • FIG. 87 depicts a plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of a given, selected sample (or Pap smear slide) categorized as Group II (or non-typical inflammation), in accordance with certain embodiments of the invention.
  • a fourth Dl plot possess the following specifications and associated analytical information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X- axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.015 to a maximum of equal to +0.02; analytical information is analysis of the fourth Dl plot (or OMF Diagram) of the digital photography image of the sample; patient information is the given, selected seventeenth patient of the Group II (or non-typical inflammation) or Group II Patient 17; test input sample is the Pap smear slide categorized as the Group II (or non-typical inflammation) of the patient referred to as Group II Patient 17; operation is implementation of OMF method on digital images of
  • FIG. 87 shows that the OMF diagram presented therein has a different diagram pattern vis-a-vis the diagrams discussed in conjunction with the FIGS. 84C, 85C and 86C.
  • Noteworthy is the fact that all higher order Pap groups can be described with distinctive diagrams depicting the characteristic intensity to wavelength relationship thereof. Particularly, noteworthy is the fact that these patterns differ in an easily detectable manner.
  • the diagram for Group II shown in FIG. 87 has one peak more than the sample from Group I. More particularly, four peaks belonging to following wavelengths: 1 12 nm, 120 nm, 128 nm and 132 nm, have intensities and wavelengths whose distribution differs from that of the group I.
  • FIG. 88 depicts a plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of a given, selected sample (or Pap smear slide) categorized as Group III (dysplasia), in accordance with certain embodiments of the invention.
  • a fifth Dl plot possess the following specifications and associated analytical information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X- axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.06 to a maximum of equal to +0.04; analytical information is analysis of the fifth Dl plot (or OMF Diagram) of the sample; patient information is a given, selected seventeenth patient of the Group III (or non-typical inflammation); test input sample is the Pap smear slide categorized as Group III of a patient referred to as Group III Patient 16; operation is implementation of OMF method on digital images of the given, selected seventeenth sample (or Pap smear slide)
  • FIG. 89 depicts a plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of a given, selected sample (or Pap smear slide) categorized as Group IV (carcinoma in situ), in accordance with certain embodiments of the invention.
  • a sixth Dl plot possess the following specifications and associated analytical information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X- axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.04 to a maximum of equal to +0.02; analytical information is analysis of the sixth Dl plot (or OMF Diagram) of the sample; patient information is a given, selected fourth patient of the Group IV (or carcinoma in situ) or Group IV Patient 4; test input sample is the Pap smear slide categorized as the Group IV (or carcinoma in situ) of the patient referred to as Group IV Patient 4; operation is implementation of OMF method on digital images of the sample; number of intensity
  • Table 5 exhibits a tabular representation in connection with parameter values of OMF study for 5 cases (carcinoma in situ) as True Positive.
  • FIG. 90 depicts a plot of a typical spectral data (or OMF diagram) obtained on implementation of the OMF method on digital images of a given, selected sample (or Pap smear slide) categorized as Group V (suspicion to carcinoma), in accordance with certain embodiments of the invention.
  • a seventh Dl plot possess the following specifications and associated analytical information thereof: ordered (or Dl) pair is (Wavelength Difference Value, Intensity Value); horizontal X-axis includes a closed interval of Wavelength Difference Values ranging from a minimum of equal to 100 nanometers (nm) to a maximum of equal to 220 nanometers (nm) (or [100, 220]); vertical X- axis includes a closed interval of Intensity Values ranging from a minimum of equal to -0.03 to a maximum of equal to +0.03; analytical information is analysis of the seventh Dl plot (or OMF Diagram) of the sample; patient information is a given, selected seventh patient of the Group V (suspicion to carcinoma) or Group V Patient 7; test input sample is the Pap smear slide categorized as the Group V (suspicion to carcinoma) of the patient referred to as Group V Patient 7; operation is implementation of OMF method on digital images of the sample; number of intensity peaks (or extrema or maxima and
  • OMF diagrams for samples categorized as Group IV (carcinoma in situ) and Group V (suspicion to carcinoma) share some qualitative similarity but differ markedly from Groups I, II, and III.
  • the difference is obvious not only in distribution of peaks within lower wavelength difference range ( ⁇ 140 nm) but also throughout the higher spectral range of wavelength differences that is captured by this method (100-220 nm).
  • the patterns in higher wavelength differences are unseen in lower grade groups and are likely to be produced by malignant cells.
  • systems for generating enhanced heterogeneous signals for use in noninvasive processing of materials using an Opto-Magnetic Antenna (or OMA), and methods thereof are disclosed.
  • system and “Opto-Magnetic Amplifier (or OMA)” are used interchangeably, unless otherwise prescribed.
  • system and “Opto-Magnetic Amplifier (or OMA)” are used interchangeably to refer to a system which has been designed and implemented herein for generating enhanced heterogeneous (or mixed) signals for use in non-invasive processing of materials.
  • first signal processing subsystem and “Opto-Magnetic Signal Processor (or OMSP)” are used interchangeably to refer to a subsystem which has been designed and implemented herein for generating spectral signatures for materials.
  • second signal processing subsystem and “Direct EM Signal Processor (or DEMSP)” are used interchangeably to refer to a subsystem which has been designed and implemented to process EM signals.
  • DEMSP Direct EM Signal Processor
  • systems and / or methods for non-invasive surface and / or bulk processing of materials have been disclosed. Specifically, such systems and / or methods for noninvasive detection, analysis, characterization, indication, identification, and determination of materials are based on valence electrons. Such systems and / or methods measure the magnetic change in the valence orbitals. This implies that such methods measure Electro-Magnetic (EM) changes in underlying structures, such as skin, collagen, elastin or a metal. Thus, such systems and / or methods can provide information about the composition of the materials. For example, theoretically such systems and / or methods can be used down to a level approximately 1 millimeter by 1 millimeter to measure material properties.
  • EM Electro-Magnetic
  • the aforementioned systems and / or methods may be implemented as an antenna amplifier. These systems and / or methods can measure the variance in the magnetic receptance of the antenna and get highly enhanced antenna reception. In certain situations involving antennae supplied with an input signal, such systems and / or methods can give a result based on the antennae properties of the input signal. In such situations, the output signal can be enhanced based on the antenna properties.
  • magnetic reception refers to sensitivity to magnetic stimuli.
  • magnetic stimuli For example, the very weak magnetic stimuli occurring naturally in the environment.
  • the data sets generated on illumination of skin with polarized light may be of less value as compared to the data sets captured using incident unpolarized light. For example, by measuring the effects between 10 "34 and 10 "30 Js measurements can be made at the border area of quantum and classical physics effects on skin and as a difference of action of electrical and magnetic forces of valence electrons of skin's biomolecules.
  • unpolarized light includes any permutations and / or combinations of diffused light, white light, monochromatic light, light of multiple single wavelengths and the like.
  • the white light is a light consisting of photons of all wavelengths.
  • photons can make the valence electrons of an atom transition to a higher electronic energy level.
  • FIG. 91 depicts a system for generating enhanced heterogeneous signals for use in non-invasive processing of materials utilizing an Opto-Magnetic Antenna (or OMA), designed and implemented in accordance with certain embodiments of the invention.
  • OMA Opto-Magnetic Antenna
  • the system 9100 is in essence an Opto-Magnetic Amplifier (or OMAMP.)
  • the OMAMP 9100 consists of the OMA 9102, a metal attachment 9104, an imaging sensor 9106, an Opto-Magnetic Signal Processor (or OMSP) 9108, a Direct Electro-Magnetic Signal Processor (or DEMSP) 91 10 and a signal combiner (or mixer) 91 12.
  • the OMAMP 9100 processes Electro-Magnetic (or EM) and photomagnetic (or photo-magnetic Optomagnetic or Opto-Magnetic) signals thereby facilitating detection, analysis, characterization, indication, identification, assessment and determination of the materials.
  • Electro-Magnetic or EM
  • photomagnetic or photo-magnetic Optomagnetic or Opto-Magnetic
  • the OMAMP 9100 can be coupled to a metallic surface (not shown), for example as a regular antenna.
  • the OMA 9102 may be a transmitting antenna.
  • the OMA 9102 transmits EM signals.
  • the OMA 9102 receives the EM signals and generates a response based on the received EM signals. It must be noted here that the output signal of the OMA 9102 can be boosted based on the response of the OMA 102.
  • the OMA 9102 is coupled to the metal attachment 9104 and the DEMSP 91 10. This is shown in FIG. 91. Specifically, the OMA 9102 feeds the EM signals to an input of the DEMSP 91 10.
  • transmitting antenna or transmitter refers to an electronic device which, usually with the aid of an antenna, propagates an EM signal, such as in radio, television, or other telecommunications applications. In other applications signals can also be transmitted using an analog 0/4 - 20 mA current loop signal.
  • the metal attachment 9104 is in essence a receiving antenna.
  • the metal attachment 9104 receives EM signals.
  • metal attachment or attachment refers to a special hardware specific to an antenna model for attachment to an antenna mounting pipe or concealment structure.
  • the antenna attachment is located at the base end of the antenna element.
  • the antenna attachment has a capacitive reactance.
  • the antenna attachment can cancel the inductive reactance of the antenna thereby causing the impedance of the antenna to approach a prescribed value.
  • the metal attachment 9104 is coupled to the OMA 9102.
  • the imaging sensor 9106 is in essence a device that converts an optical image to an electric signal.
  • the imaging sensor 9106 captures continuous digital images of the metallic surface. Noticeable here is the fact that the OMAMP 9100 is attached to the metallic surface. Specifically, in such embodiments, the imaging sensor 9106 captures continuous digital images of the metallic surface illuminated with white light both, non-angled and angled.
  • the imaging sensor 106 may be anyone selected from a group consisting of a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor, Charged Coupled Device (CCD) image sensor, and the like.
  • CMOS Complementary Metal-Oxide-Semiconductor
  • CCD Charged Coupled Device
  • the imaging sensor 9106 is coupled to the metal attachment 9104, as depicted in FIG. 91.
  • the imaging sensor 9106 is coupled to the OMSP 9108.
  • an output of the imaging sensor 9106 is coupled to an input of the OMSP 9108.
  • digital image refers to a representation of a two-dimensional image using ones and zeros (or binary digits or bits).
  • the digital image may be of vector or raster type depending on whether or not the image resolution is fixed. However, without qualifications the term “digital image” usually refers to raster images.
  • the imaging sensor 9106 may be selected on the basis of the following specifications: color is color or monochrome; optical format; horizontal pixels X vertical pixels; pixel size; one or more performance parameters, such as maximum frame rate, data rate, maximum power dissipation, quantum efficiency, dynamic range and supply voltage; output; one or more features, such as integrated Analog-to-Digital Converter (ADC) and microlenses; and environment, such as operating temperature.
  • ADC Analog-to-Digital Converter
  • the OMSP 9108 may be a customized digital signal processor.
  • the OMSP 9108 has a single input and a single output. [00771] The OMSP 9108 processes the continuously captured non-angled and angled white light digital images of the metallic surface.
  • the process of generating a spectral signature for materials and the system thereof (for implementing or facilitating implementation of) the process is disclosed, in accordance with the principles of the invention.
  • the OMSP 9108 implements the process of generating the spectral signature for materials.
  • the process comprises the stages of capturing an image of a material illuminated with incident non-angled and angled white light, generating a normalized red and blue color channel histogram for each image, correlating the normalized red and blue color channel histograms to a wavelength scale to obtain red and blue color channel spectral plots, and convoluting the spectral plots by subtracting the spectral plot for angled light from the spectral plot for non-angled light for each color channel to generate red and blue normalized, composite color channel spectral plots, and subtracting the normalized, composite blue channel spectral plot from the normalized, composite red channel spectral plot to generate a spectral signature for the material.
  • the OMSP 108 implements a process for generating the spectral signature for materials as disclosed in United States Provisional Patent Application "METHOD AND ALGORITHM FOR ANALYSIS OF LIGHT- MATTER INTERACTION BASED ON SPECTRAL CONVOLUTION" to MYSKIN, INC., the disclosure of which is incorporated herein by reference in its entirety. Thus, all remaining ins-and-outs in connection with the process of generating the spectral signature will not be further detailed herein.
  • the input of the OMSP 9108 is coupled to the output of the imaging sensor 9106.
  • the input of the OMSP 9108 is fed with the continuously captured non-angled and angled white light digital images of the material.
  • the output of the OMSP 9108 generates Opto-Magnetic signals.
  • the output of the OMSP 9108 is coupled to the signal combiner 91 12.
  • digital image processing refers to the use of computer algorithms to perform image processing on digital images.
  • digital image processing has many advantages over analog image processing. For example, digital image processing allows a much wider range of algorithms to be applied to the input data and can avoid problems, such as the build-up of noise and signal distortion during processing.
  • spectral signatures refers to specific combination of reflected and absorbed electromagnetic radiation at varying wavelengths that can uniquely identify an object.
  • the spectral signature of an object is a function of incidental Electro-Magnetic (EM) wavelength and material interaction with that section of the electromagnetic spectrum.
  • EM Electro-Magnetic
  • the measurements can be made with various instruments, including but not limited to, a task specific spectrometer. For instance, the most common method is separation of the Red (R), Green (G), Blue (B) and Near Infrared (NIR) portion of the EM spectrum as acquired by digital cameras.
  • R Red
  • Green Green
  • B Blue
  • NIR Near Infrared
  • Antenna tuning is done by adjusting an inductance or capacitance combined with the active antenna (but distinct and separate from the active antenna).
  • the inductance or capacitance provides the reactance which combines with the inherent reactance of the active antenna to establish a resonance in a circuit including the active antenna.
  • the established resonance being at a frequency other than the natural electrical resonant frequency of the active antenna. Adjustment of the inductance or capacitance changes this resonance.
  • Antennas used for transmission have a maximum power rating, beyond which heating, arcing or sparking may occur in the components, which may cause them to be damaged or destroyed. Raising this maximum power rating usually requires larger and heavier components, which may require larger and heavier supporting structures. This is a concern only for transmitting antennas, as the power received by an antenna rarely exceeds the microwatt range.
  • Antennas designed specifically for reception might be optimized for noise rejection capabilities.
  • An antenna shield is a conductive or low reluctance structure (such as a wire, plate or grid) which is adapted to be placed in the vicinity of an antenna to reduce, as by dissipation through a resistance or by conduction to ground, undesired electromagnetic radiation, or electric or magnetic fields, which are directed toward the active antenna from an external source or which emanate from the active antenna.
  • Other methods to optimize for noise rejection can be done by selecting a narrow bandwidth so that noise from other frequencies is rejected, or selecting a specific radiation pattern to reject noise from a specific direction, or by selecting a polarization different from the noise polarization, or by selecting an antenna that favors either the electric or magnetic field.
  • an antenna to be used for reception of low frequencies will be subject to both man-made noise from motors and other machinery, and from natural sources such as lightning. Successfully rejecting these forms of noise is an important antenna feature.
  • a small coil of wire with many turns is more able to reject such noise than a vertical antenna.
  • the vertical will radiate much more effectively on transmit, where extraneous signals are not a concern.
  • tuning refers to adjusting a device to a desired frequency.
  • Additive mixers add two or more input (or source) signals thereby outputting a composite signal that contains the frequency components of each of the input signals.
  • the simplest additive mixers are simple resistor networks, and thus purely passive, whereas more complex mixers employ active components such as, buffer amplifiers for impedance matching and better isolation.
  • the multiplying mixers multiply two or more input (or source) signals together thereby producing an output containing both the input signals and new signals that comprise the sum and difference of the frequency of the input signals.
  • ideal product mixers act as signal multipliers thereby producing an output signal equal to the product of the input signals.
  • the product mixers are often used in conjugation with an oscillator to modulate signal frequencies.
  • the product mixers can either up-convert or down- convert an input signal frequency, but it is more common to down-convert to a lower frequency to allow for easier filter design.
  • the single output signal actually contains multiple waveforms, namely those at the sum and difference of the two input frequencies and harmonic waveforms.
  • the ideal signal may be obtained by removing the other signal components with a filter.
  • the DEMSP 9110 has a single input and a single output.
  • the DEMSP 9110 may be a customized Analog Signal Processor (ASP).
  • ASP Analog Signal Processor
  • the DEMSP 91 10 may employ analog signal processing to process the EM signals.
  • analog signal processing refers to any signal processing conducted on analog signals by analog means.
  • analog signal processing include crossover filters in loudspeakers, “bass”, “treble” and “volume” controls on stereos, and “tint” controls on TVs.
  • Common analog processing elements include capacitors, resistors, inductors and transistors.
  • the input of the DEMSP 91 10 is fed with the EM signals.
  • the input of the DEMSP 9110 is coupled to the OMA 9102.
  • the output of the DEMSP 91 10 outputs unenhanced signals.
  • the output of the DEMSP 9110 is coupled to the signal combiner 91 12.
  • the signal combiner 91 12 combines (or mixes) two or more signals into one composite output signal.
  • the signal combiner 91 12 consists of a pair of inputs and a single output.
  • the first input of the pair of inputs of the signal combiner 91 12 is coupled to the DEMSP 91 10.
  • the first input of the pair of inputs of the signal combiner 91 12 is fed with the unenhanced signal.
  • the second input of the pair of inputs of the signal combiner 9112 is coupled to the OMSP 9108.
  • the second input of the pair of inputs of the signal combiner 91 12 is fed with the Opto-magnetic signal.
  • the signal combiner 91 12 combines (or mixes) the unenhanced signal from the DEMSP 9110 and the Opto-magnetic signal from the OMSP 9108 thereby producing the enhanced signal.
  • the OMAMP 9100 is coupled to a test material surface.
  • the imaging sensors 9106 capture continuous digital images of the material illuminated with non-angled and angled white light.
  • the output of the imaging sensors 9106 is fed as input to the OMSP 9108.
  • the OMSP 9108 processes the continuously captured digital images of the material to generate a spectral signature of the material, in accordance with the principles of the invention disclosed earlier.
  • the antenna 9102 transmits EM signals to the DEMSP 91 10.
  • the DEMSP 91 10 processes the EM signals and outputs an unenhanced EM signal.
  • the output of the OMSP 9108 i.e. the Opto-Magnetic signal
  • the output of DEMSP 91 10 i.e. the unenhanced EM signal
  • the signal combiner 91 12 combines (or mixes) the Opto-Magnetic signal and unenhanced EM signal to generate an enhanced mixed signal.
  • the wavelengths and algorithm varies by the frequency of the target antenna.
  • Multiple detectors may be placed on the same metal surface in order to take images in parallel in order to increase processing speed based on wavelength, etc. Tuning to different frequencies is done by analyzing the resulting spectrum as well as adjusting the speed of the images taken.
  • design and implementation of one or more workable configurations for the system of FIG. 91 for facilitating high frequency imaging and processes thereof have been disclosed.
  • such configurations can use multiple sensors that allow rapid lighting sequences for rapid imaging thereby resulting in high frequency imaging of materials.
  • FIG. 92 is block diagrammatic view of at least one workable configuration for use in tandem with the system of FIG. 91.
  • the configuration 9200 comprises the OMA 9102, metal attachment 9104, at least two pairs of the imaging sensors 9106 and a timing module 9202.
  • the configuration 9200 may be coupled to surface of materials.
  • materials may be anyone selected from a group of both inorganic and organic materials consisting of skin, collagen, elastin, metal and the like.
  • the two pairs of imaging sensors 9106 consists of a first imaging sensor 9106A, second imaging sensor 9106B, third imaging sensor 9106C and fourth imaging sensor 9106D.
  • each individual sensor 9106 of the two pairs of imaging sensors 9106 captures continuous digital images of materials illuminated with the unangled and angled white light.
  • Timing module (or Timer) 9202 is a specialized type of clock.
  • the timer 9202 can be used to control the sequence of an event or process.
  • the configuration 9200 implements a process facilitating high frequency imaging of materials by employment of multiple sensors. Specifically, the process implements a sequence of process stages of imaging for rapid imaging using the multiple sensors. It must be noted here that the use of the multiple sensors allow rapid lighting sequences thereby resulting in high frequency imaging of materials. This sequence has been explained in conjunction with the process of FIG. 93 and TABLE 1 .
  • the timing module 9202 is separately coupled to each individual sensor 9106 of the two pairs of the imaging sensors 9106.
  • the system configuration implement one or more processes facilitating high frequency imaging by employment of multiple sensors.
  • the processes comprise one or more sequences of process stages of imaging for rapid imaging using the multiple sensors. It must be noted here that the use of the multiple sensors allow rapid lighting sequences thereby resulting in high frequency imaging of materials.
  • FIG. 93 depicts a flow diagram delineating at least one process implemented by the system configuration of FIG. 92 thereby facilitating multi sensor high frequency imaging.
  • the process 9300 starts at stage 9301 and proceeds to stage 9302, where the process 9300 comprises the phase of capturing images of a material illuminated with a white light (or unangled white light.) Noticeable here is the fact that the process 9300 initiates the first imaging sensor for capturing images of the material illuminated with the white light.
  • the process 9300 comprises the phase of capturing images of the material illuminated with an angled white light.
  • the process 9300 initiates the first imaging sensor for capturing images of the material illuminated with the angled white light.
  • the process 9300 comprises the phase of capturing images of the material illuminated with the white light. It must be noted here that the process 9300 initiates the second imaging sensor for capturing images of the material illuminated with the white light.
  • the process 9300 comprises the phase of capturing images of the material illuminated with the angled white light using the second imaging sensor.
  • the process 9300 comprises the phase of capturing images of the material illuminated with the white light using the third imaging sensor.
  • the process 9300 comprises the phase of capturing images of the material illuminated with the angled white light using the third imaging sensor.
  • the process 9300 comprises the phase of capturing images of the material illuminated with the white light using the fourth imaging sensor.
  • the process 9300 comprises the phase of capturing images of the material illuminated with the angled white light using the fourth imaging sensor.
  • the process 9300 ends at the stage 9318. It is worth notable that the timer 9202 can be used to control the sequence of the process 9300.
  • Table 6 below provides at least one sequence of imaging for rapid imaging.

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Abstract

La présente invention concerne généralement des procédés et systèmes de détermination des propriétés magnéto-optiques de la lumière réfléchie par des matières alimentaires. Lesdites propriétés magnéto-optiques peuvent être utilisées pour générer une empreinte d'identification magnéto-optique. La comparaison de l'empreinte d'identification magnéto-optique à des empreintes d'identification magnéto-optiques de matières connues permet de caractériser les matières alimentaires. Ceci permet de détecter des résidus de pesticides, de confirmer une certification biologique et de déterminer la fraîcheur des matières alimentaires.
PCT/US2012/038534 2011-05-19 2012-05-18 Caractérisation de matières alimentaires par identification magnéto-optique WO2012159012A1 (fr)

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US61/488,085 2011-05-19

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CN110168668A (zh) * 2016-08-25 2019-08-23 德国史密斯海曼有限责任公司 具有集成更换指示件的辐射屏蔽元件
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Cited By (14)

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Publication number Priority date Publication date Assignee Title
US10085643B2 (en) 2007-01-05 2018-10-02 Jadran Bandic Analytic methods of tissue evaluation
US9234081B2 (en) 2010-06-08 2016-01-12 King Abdulaziz City For Science And Technology Method of manufacturing a nitro blue tetrazolium and polyvinyl butyral based dosimeter film
US9932959B2 (en) 2011-03-10 2018-04-03 King Abdulaziz City For Science And Technology Shrounded wind turbine configuration with nozzle augmented diffuser
CN104535732A (zh) * 2015-02-09 2015-04-22 蒋和平 基于物联网的食品安全检测系统
WO2017025970A1 (fr) * 2015-08-12 2017-02-16 Yeda Research And Development Co. Ltd. Détection de sources ponctuelles d'intensité d'émission variable dans des séquences d'images avec différentes fonctions d'étalement de points
US10776653B2 (en) 2015-08-12 2020-09-15 Yeda Research And Development Co. Ltd. Detection of point sources with variable emission intensity in sequences of images with different point spread functions
CN110168668A (zh) * 2016-08-25 2019-08-23 德国史密斯海曼有限责任公司 具有集成更换指示件的辐射屏蔽元件
CN110168668B (zh) * 2016-08-25 2024-03-12 德国史密斯海曼有限责任公司 具有集成更换指示件的辐射屏蔽元件
RU2638910C1 (ru) * 2016-12-14 2017-12-18 Федеральное государственное бюджетное учреждение науки Институт космических исследований Российской академии наук Способ экспресс-контроля объекта
US11574739B2 (en) 2018-01-29 2023-02-07 Function, Inc. Systems and methods for formulating personalized skincare products
US10546658B2 (en) * 2018-01-29 2020-01-28 Atolla Skin Health, Inc. Systems and methods for formulating personalized skincare products
CN110159265A (zh) * 2018-02-13 2019-08-23 中国石油天然气股份有限公司 确定非均质储层的含油饱和度的方法及装置
US10832094B2 (en) 2018-04-10 2020-11-10 International Business Machines Corporation Generating hyperspectral image database by machine learning and mapping of color images to hyperspectral domain
WO2020092648A1 (fr) * 2018-10-30 2020-05-07 Teakorigin Inc. Techniques de notation d'échantillons d'aliments, et procédé et appareil s'y rapportant

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