WO2003010510A2 - Systeme et procede quantitatif d'ajout pour mesure non invasive d'analytes in vivo - Google Patents
Systeme et procede quantitatif d'ajout pour mesure non invasive d'analytes in vivo Download PDFInfo
- Publication number
- WO2003010510A2 WO2003010510A2 PCT/US2002/023348 US0223348W WO03010510A2 WO 2003010510 A2 WO2003010510 A2 WO 2003010510A2 US 0223348 W US0223348 W US 0223348W WO 03010510 A2 WO03010510 A2 WO 03010510A2
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- tissue
- adjunct
- patient
- analyte
- spectral
- Prior art date
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/1495—Calibrating or testing of in-vivo probes
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
Definitions
- the invention relates to a method and apparatus for the non-invasive measurement of in vivo analytes in a patient. Particularly, the invention relates to the use of a combination of one or more spectroscopic measurements combined with an adjunct spectroscopic or non-spectroscopic measurement for the measurement of analytes in a tissue of a patient.
- Diabetes mellitus is a chronic life threatening disease for which there is presently no cure. It is the sixth-leading cause of death by disease in the United States, and approximately 190,000 Americans per year will die as a result of diabetes and its complications. Adopting a more global perspective, diabetes represents an enormous challenge insofar as it now afflicts an estimated 100 million people worldwide. Diagnostically characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both, diabetes is now generally recognized as a group of metabolic diseases that share a common presentation and pathophysiology.
- Type I diabetes (juvenile diabetes or insulin-dependent diabetes mellitus) is the most severe form of the disease comprising approximately 10% of the diabetes cases in the United States. Type I diabetics must receive daily injections of insulin in order to sustain life. Type II diabetes, also known as adult onset diabetes or non-insulin dependent diabetes mellitus, comprises the other 90% of the diabetes cases. Type II diabetes is often manageable with dietary modifications and physical exercise, but may still require treatment with insulin or other medications.
- diabetes represents a well-described entity
- other target populations are also at risk for hyperglycemic episodes.
- IGT impaired glucose tolerance
- IGF impaired fasting glucose
- glucose has consistently been an obvious target for helping diabetics achieve and maintain normal blood glucose levels.
- Some devices involve self-monitoring of glucose levels by a diabetic individual and can be performed at home, and many products for self-monitoring of blood glucose levels are available commercially. Upon recommendations by doctors and using such products, patients are typically instructed to measure blood glucose levels several times a day as a way to monitor their success in controlling blood sugar levels. Nevertheless, many diabetics do not measure their blood glucose regularly.
- the existing monitoring products may be complicated, inconvenient, costly and painful, requiring a pinprick every time a measurement is made. Furthermore, these products may also require some skill, dexterity, and discipline to obtain useful measurements.
- glucometers Widespread awareness of the importance of maintaining normal glucose levels in all diabetics has prompted a wave of research and development efforts into new glucometers, which embrace less invasive techniques. As noted, most of the commercially available glucometers for home use require that blood be withdrawn. Newer approaches are focusing on minimally or non-invasive technologies that would encourage diabetic self-monitoring based on ease of use and freedom from discomfort.
- One minimally invasive glucometer that is approved for adjunctive use relies on reverse iontophoresis, wherein the diabetic wears a proprietary patch on the skin of the arm across which a current is intermittently pulsed thereby modifying the normal epidermal permeability barrier and allowing interval sampling of interstitial fluid.
- a variety of companies are pursuing alternative approaches to gain access to the interstitial fluid space via laser or needle microporation, chemical dissolution of the epidermal permeability barrier, or microdialysis.
- Optical spectroscopy has attracted interest as well, including approaches relying on either Raman, near-, mid-, or far-IR. Other innovative approaches are based on microvascular changes in the retina, acoustical impedance, NMR spectroscopy and optical hydrogels that quantify glucose levels in tear fluid.
- IR-based methodologies can be utilized to accurately quantitate a variety of in vivo parameters such as skin hydration, skin pH, skin perfusion, oxygenation, and skin temperature.
- signal modification from water and matrix components of the blood, such as hemoglobin, plus optical scatter contribute to large signal-to-noise difficulties that have resulted in variation and error in measurements.
- the instant invention which combines spectral and non-spectral measurements and techniques to measure biological analytes, such as glucose.
- the invention provides a method and apparatus to supplement ultraviolet-visible fluorescence measurements with one or more additional or adjunct measurements for quantitating an analyte, such as glucose.
- a preferred embodiment of this invention is directed to a method for the in vivo measurement of at least one biological analyte through tissue exposure to radiation, followed by spectroscopic analysis, preferably selectively evaluating ultraviolet and/or visible light fluorescence, in combination with at least one adjunctive optical measurement selected from the group comprising infrared (IR) which includes near infrared (MR), mid infrared (MIR) and far infrared (FIR), visible light absorbance,
- IR infrared
- MR near infrared
- MIR mid infrared
- FIR far infrared
- the spectroscopic measurement is combined with at least one adjunct physiological parameter measurement and/or at least one adjunct informational parameter measurement.
- adjunct measurements can also be utilized to accomplish and/or enhance the calibration of an analyte level quantitation device.
- An advantage of the above embodiment is that robustness, sensitivity,specificity, and/or accuracy are added to the non-invasive measurement of the analyte (e.g. glucose), thereby reducing the error of the measurement.
- the technology has a clearly viable miniaturization and cost reduction strategy.
- Another advantage of the invention is that the signals detected from water absorption, blood components such as hemoglobin absorption, and optical scatter, which are potential sources of variation and error in measurements, are accounted for, rather than factoring their variance into measurements as error.
- the invention provides a method of determining a level of at least one analyte in a tissue comprising: exposing the tissue with an excitation radiation from an excitation source; detecting a spectral emission or absorption from the excited or illuminated tissue; determining an adjunct parameter selected from the group comprising: at least one adjunct spectral emission; at least one adjunct physiological determinant; at least one adjunct informational determinant; and a combination thereof; combining the spectral emission detected with the adjunct parameter determined, and determining the level of said at least one analyte in the tissue.
- the excitation source provides electromagnetic radiation such as fluorescence, visible light, ultraviolet radiation, IR radiation such as FIR, MIR or R, microwaves and combinations thereof.
- the source preferably comprises exposing said tissue and exciting a target within the tissue.
- the target is a structural, cellular, matrix, or molecular species in a patient.
- the structural, cellular, matrix, or molecular species is selected from the group comprising pepsin- or collagenase-digestible collagen cross links, non-pepsin digestible collagen cross links, tryptophan, elastin, elastin cross-links, keratin, serum proteins, Glu-T proteins, NADH, NADPH, flavoproteins (e.g. FAD), melanin precursors, porphyrins (e.g. including hemoglobin, glycosylated hemoglobin Ale, or red blood cells), cytochrorhes, vitamin B complexes, carotenoid, salicylate (aspirin), lactate, pyruvate, ketones (e.g.
- acetoacetate and beta-hydroxybutyrate free fatty acids, succinate, fumarate, dihydroxyacetone phosphate (DHAP), 3-phosphoglycerate, acetyl.
- CoA succinyl CoA, alpha-ketoglutarate, malate, citrate, isocitrate, bicarbonate, insulin, triglyceride, cholesterol, phosphorus, calcium, blood urea, electrolytes, bilirubin, creatinine, albumin, lactate dehydrogenase (LDH), and combinations thereof.
- the level of the at least one analyte is a relative or an absolute amount.
- At least one analyte is selected from the group comprising glucose, NADH, NADPH, FAD, tryptophan, collagen, elastin, salicylate (aspirin), lactate, pyruvate, ketones (acetoacetate and beta-hydroxybutyrate), free fatty acids, succinate, fumarate,
- DHAP 3-phosphoglycerate, acetyl CoA, succinyl CoA, alpha-ketoglutarate, malate, citrate, isocitrate, bicarbonate, insulin, hemoglobin, glycosylated hemoglobin Ale, triglycerides, cholesterol, phosphorus, calcium, blood urea, electrolytes, bilirubin, creatinine, total protein, albumin, LDH, blood gases, cholesterol, alcohol, medications, pharmaceuticals, narcotics (e.g. cocaine), and/or poisons (e.g. cyanide).
- the tissue is selected from the group comprising human tissue, animal tissue, forensic tissue, skin, soft tissue of the mouth, ear lobe tissue, internal body tissue, eye tissue, tissue in or around an eye, internal organ tissue, a whole organism and combinations thereof.
- the excitation radiation is at a wavelength between about 295 nm to about
- the excitation radiation is at a wavelength between about 320 nm to about 700 nm. Even more preferably, the excitation radiation is at a wavelength between about 320 nm to about 510 nm.
- the excitation source is a visible light source, a laser source, a microwave source, a discharge light source, an incandescent light source, a light emitting diode
- LED LED
- a fluorescent light source LED
- the spectral emission or absorption is IR, Ramen, ultraviolet, visible, or fluorescence radiation.
- at least one spectral emission is detected at a wavelength between about 295 nm to about 700 nm.
- the spectral emission comprises measuring one or more spectral characteristics of the excited target selected from the group comprising fluorescence life-time, wavelength, intensity including peak heights and peak areas, relative peak ratios, spectral shapes, peak shifts, band narrowing, spectral kinetics, band broadening, scattering, polarization and combinations thereof.
- the spectral emission is performed substantially simultaneously with determination of said adjunct parameter.
- the detection of the spectral emission is performed substantially sequentially with determination and/or data entry of the adjunct parameter.
- the selected target and detection of the spectral emission are performed at the same or different locations of said tissue.
- At least one adjunct physiological determinant is determined by a passive or active procedure.
- At least one physiological determinant comprises a combination of one or more local or systemic determinants selected from a group comprising: oxygen saturation (arterial and/or venous), temperature, blood volume, one or more blood chemical determinants, blood volume change, blood pressure, cardiac output, blood flow, pulsatile effects, pH, skin perfusion, hydration, vasodilation, nitric oxide (NO), metabolic index, or respiratory function parameters (e.g., oxygen partial pressure and carbon dioxide partial pressure), as well as other tissue optical properties, such as contact pressure/optical interface, tissue color, tissue homogeneity, skin roughness, skin stretch, skin tone, ultraviolet effects, ultraviolet dosage, and the like, and combinations thereof.
- At least one informational determinant is a combination of one or more determinants selected from the group comprising date, time of day, period of time since last meal, content of last meal, insulin dosing information (e.g. period of time since last insulin inj ection, dosage of last insulin injection, insulin pump data), age of the patient, skin age of the patient, skin AGE determination, skin color, gender, menstrual history, weight, percent body fat, exercise/activity level, pulse rate, type of diabetes, duration of diabetes, type and dosage of non-insulin medications, medical complications secondary to diabetes, pertinent additional medical and family history, aspirin usage, tobacco and/or alcohol usage, blood/serum osmolarity and analyte determination category.
- the informational determinant will also include pulse oximetry data reflecting relative or absolute levels of oxy:deoxyhemoglobin.
- calibrating the spectral information against one or more other spectral emissions from said target using one or more multivariate techniques Preferably, calibrating the spectral information against one or more other spectral emissions from said target using one or more multivariate techniques.
- the instant method further comprises detecting a vibrational-spectroscopic emission from the excited tissue.
- the vibrational-spectroscopic emission is collected at a frequency common to the detected spectral emission.
- the instant invention provides an apparatus for determining a level of at least one analyte in a tissue comprising: a light source for exciting a target in the tissue with excitation radiation; a detector for detecting at least one spectral emission from the excited target; a determining means for determining, recording or collecting an adjunct parameter; and a means for combining said spectral emission detected with said adjunct parameter to obtain the level of the at least one analyte in the tissue.
- the instant apparatus further comprises a display element, wherein said display element displays the level of the at least one analyte in the tissue.
- the instant apparatus further comprises a transmitting means for transmitting data pertaining to the detected spectral emission, the adjunct parameter, the level of the at least one analyte, or any combination thereof.
- the excitation radiation is at a wavelength selected in a range from about 295 nm to about 1100 nm.
- the detection means detects emission radiation at one or more wavelengths in the range from about 295 nm to 700 nm.
- the instant apparatus further comprises an audio generator, wherein said audio generator generates one or more sounds when said level at least one analyte is determined.
- the means for combining is a processor.
- the processor comprises an algorithm to combine said spectral emission and adjunct parameter.
- the instant apparatus further comprises a memory.
- Optical information from tissue can be used to indicate the physiological state of the tissue and often the patient from which the tissue was obtained.
- IR such as near-IR methods can be utilized to quantitate a number of useful in vivo parameters such as skin hydration, skin pH, skin perfusion, and oxygenation, as well as skin temperature. Many of these parameters can be quantitated using commercially available instrumentation.
- signals seen from water absorption, or blood signals such as hemoglobin absorption and/or scattering are potential sources of variation and error in measurements.
- the phenomenon of endogenous skin fluorescence, as well as endogenous fluorescence of other biological tissues, is well known in the field.
- the fluorophores responsible for skin autofluorescence in the ultraviolet and blue regions of the spectrum include metabolic components and intermediates, plus proteins and collagen.
- tryptophan which fluoresces in the 295-350 nanometer (nm) region
- keratin which fluoresces in the 295-340 nm region
- NADH nicotinamide adenine dinucleotide
- FAD flavin adenine dinucleotide
- fluorophores associated with collagen cross-links which fluoresce in a broad region from 420 to 490 nm.
- the collagen cross-link fluorophores are thought to arise through a number of possible chemical transformations, including the Maillard reaction, into stable entities known as advanced glycosylation end products (AGE's). These AGE's form at a higher rate in people with diabetes presumably because of chronic exposure to elevated of tissue glucose levels.
- the present invention provides methods and devices for in vivo quantitation and trend analysis of biological analyte concentrations in tissue.
- the present invention is directed to a methodology and apparatus that is able to combine ultraviolet and visible light spectral analyses with one or more other spectroscopic techniques and/or one or more physiological measurements and/or informational parameters for the purpose of improving analyte level determination.
- the invention is directed to measuring a level of at least one analyte in a patient, which is usually a mammal and preferably a human, that is accomplished by exciting a target in a tissue by radiation and performing at least one spectroscopic visible or ultraviolet light fluorescence emission measurement.
- Analytes that may be detected by methods of the instant invention include, but are not limited to, glucose, NADH, NADPH, FAD, tryptophan, collagen, elastin, salicylate (i.e. aspirin), lactate, pyruvate, ketones (e.g. acetoacetate and beta-hydroxybutyrate), free fatty acids, succinate, fumarate, dihydroxyacetone phosphate (e.g.
- DHAP 3- phosphoglycerate, acetyl CoA, succinyl CoA, alpha-ketoglutarate, malate, citrate, isocitrate, bicarbonate, insulin, hemoglobin, glycosylated hemoglobin Ale, triglycerides, cholesterol, phosphorus, calcium, blood urea, electrolytes, bilirubin, creatinine, total protein, albumin, lactate dehydrogenase (LDH), blood gases, cholesterol, alcohol, medications, narcotics, and/or poisons (e.g. cyanide).
- LDH lactate dehydrogenase
- Suitable targets are those that reflect alterations within the environment of matrix components of the skin or other tissue and are sensitive to, or correlate with, analyte levels when exposed to ultraviolet or visible light radiant energy.
- ratiometric analysis of multiple targets e.g. NADH/FAD or oxy/deoxyhemoglobin
- adjunct data e.g. integrating adjunct data in a ratiometric fashion which contribute information about local environmental perturbations that similarly are sensitive to, or correlate with, analyte levels when exposed to ultraviolet or visible light radiant energy.
- spectral information obtained by excitation with ultraviolet or visible radiation can be combined with pulse oximetry data to yield specific analyte and/or physiological information.
- a target may be a quencher and yield a characteristic signal which can be correlated with an analyte level.
- Fluorescence quenching is a process which decreases the intensity of the fluorescence emission.
- the accessibility of groups on a protein molecule can be measured by use of quenchers to perturb fluorophores and decrease fluorescence. Quenching may occur by several mechanisms which include collisional or dynamic quenching, static quenching, quenching by energy transfer, or charge transfer reactions. Data provided by pulse oximetry may be a useful adjunct for correlating analyte levels with quenching signal profiles.
- targets for excitation include structural, cellular, matrix or molecular tissue components or combination of components of the patient.
- the targets include, but are not limited to, the skin or any of its components or appendages, such as pepsin- or collagenase-digestible collagen cross links, non-pepsin digestible collagen cross links, tryptophan, elastin, elastin cross-links, keratin, serum proteins, Glu-T proteins, NADH, NADPH, flavoproteins (e.g.
- FAD melanin precursors
- porphyrins including hemoglobin, glycosylated hemoglobin Ale, or red blood cells
- cytochromes some vitamin B complexes
- other chromophores such as carotenoids, and combinations thereof.
- Other preferred targets may include salicylate (aspirin), lactate, pyruvate, ketones (acetoacetate and beta-hydroxybutyrate), free fatty acids, succinate, fumarate, dihydroxyacetone phosphate (DHAP), 3-phosphoglycerate, acetyl CoA, succinyl CoA, alpha-ketoglutarate, malate, citrate, isocitrate, bicarbonate, insulin, triglycerides, cholesterol, phosphorus, calcium, blood urea, electrolytes, bilirubin, creatinine, total protein, albumin, lactate dehydrogenase (LDH), and combinations thereof that are related to, sensitive to, or co-vary with analyte concentration.
- salicylate aspirin
- lactate lactate
- pyruvate ketones
- ketones acetoacetate and beta-hydroxybutyrate
- free fatty acids succinate
- succinate fumarate
- DR diffuse reflectance
- optical coherence tomography utilizes back-scatter from spatial structures for imaging purposes and laser doppler velocimetry utilizes the temporal nature of the scattered light to ascertain velocity information.
- spatial scatter profiles provide cell size information.
- the large number and varying distributions of different types of scatter centers as well as variations in the refractive index of the surrounding medium will complicate the precise nature of scatter in such media.
- the wavelength used, optical polarization, angle of illumination, and the way in which the diffuse reflected light is detected can have a significant impact on the nature of the spectrum.
- a convenient way to describe a diffuse reflected spectrum is to take the logarithm of the ratio the signal to the incident energy spectrum.
- transmission absorption spectroscopy this is routinely done to provide estimates of concentrations of absorbers in the medium when the Beer-Lambert law is know to apply.
- Beer-Lambert law does not apply in tissue reflectance studies, it is a useful transformation.
- the resulting "absorbance" spectrum contains features that may be useful in identifying constituent components although quantification must also be addressed because: (1) scatter introduces a loss mechanism whereby the absorbance spectrum exhibits 'apparent' absorption characteristics even in the absence of truly absorbing chromophores and this loss mechanism is wavelength dependent, (2) scatter gives rise to a distribution of path length samplings (also wavelength dependent) whereby concentrations of true chromophores present in the medium can not be simply extracted from the absorbance spectrum and knowledge of the chromophores extinction coefficient, (3) the absorbance spectrum can be very dependent on the configuration used to measure the DR spectrum, and (4) temporal variations in the scatter environment will have nonlinear affects on the distribution of path lengths with consequent further complications in chromophore concentration extraction and apparent absorption due to scatter.
- the DR spectrum is an optical measurement of the same tissue region from which auto-fluorescence arises and hence enhances the accuracy, specificity and sensitivity of analyte measurements, including glucose.
- Instrument performance requirements may differ between DR and fluorescence measurements in the following areas: (1) resolution of the spectrometer (depending on use of DR spectrum); (2) dynamic range of detector; (3) reference measurement; and (4) interface probe design.
- DR can provide a way to track such temporal changes and correct fluorescent spectra for these changes.
- probe interface instabilities motion- related artifacts
- Additional sources may arise from temporal changes in the tissue biology.
- DR can provide a way to track such temporal changes and correct fluorescent spectra for these changes.
- DR will provide additional information directly relating to the optical properties of the individuals' skin (the same properties that affect fluorescence) that may provide a more quantifiable means for distinguishing between individuals. This may, for example, provide for one type of model vs. another. This then would lead to improved model stability.
- Possible means of classifying DR spectra include the correlation of selected parts or all of the DR spectrum with various measured quantities such as fluorescence intensity across individuals or sites, sites within an individual, individuals alone, a measure of skin color, temperature, pressure, perfusion, arm position, etc.
- Parameters measuring the oxygenation state of blood and blood volume can be determined from a DR spectrum.
- the utility of this information for glucose prediction arises from the fact that glucose is delivered to tissues via blood.
- DR is affected by changes in scatter and absorption. These, in turn, can be caused by refractive index variations (caused by analyte concentration changes, hydration changes, temperature changes, etc.), particle (cells and their components) size changes, and chromophore concentration changes (e.g. absorption) that correlate to physiological state of the tissue.
- these parameters can be integrated into the dataset to yield information relating to dynamic blood flow, metabolic activity, exercise tolerance, and other physiological conditions that can be mapped by analyte flux.
- DR spectral information derived either statically or in serial sets can facilitate blood flow corrections that correct for local vs. systemic processes.
- the use of perfusion information as an adjunct may provide useful information as to the effects of oxy- and deoxyhemoglobin on the spectra collected. Additionally, perfusion information can provide information as to the delivery and uptake of nutrients and the removal of metabolic byproducts. These parameters can be useful in determining analyte levels.
- a fluorescence spectra of a given patient is obtained by choosing at least one excitation wavelength from the UV- visible region, exposing between about 295 nm and 1100 nm, preferably between 320 nm and 700 nm and most preferably between 320 nm and 510 nm, and collecting the emission spectra at one or more wavelengths, most preferably in the region from 320 nm to 650 nm.
- any range or number of distinct or overlapping wavelength ranges can be selected for excitation or collection depending on the desired target within the tissue and the selected spectral emission to be analyzed.
- the step for measuring fluorescence comprises analyzing one or more parameters relating to fluorescence life-time, wavelength, intensity, peak location, relative peak ratio, spectral shape, peak width, peak shift, band narrowing, fluorescence kinetics, band broadening, scattering, phase, time, polarization, and the like, or combinations thereof.
- changes in analyte concentration which are expected to be associated with reversible changes in observable fluorescence of a target can be detected and analyzed. These changes may be due, in part, to direct and/or indirect effects of an analyte or other molecules on the environment.
- Analyte molecules in the environment may be covalently or non-covalently coupled to a target, may affect a target without binding, or may simply exist unbound in the immediate vicinity of a target.
- the fluorescence of the target may remain constant and the effects of the environment or the intervening tissue may influence the signal recorded, or both the fluorescence of the target and intervening effects may change and produce data that can be seen to co-vary with analyte levels.
- spectroscopic measurements are combined with at least one adjunctive measurement.
- An adjunct measurement or parameter is any information or data that aids and/or improves an analyte quantitation technique, such as ultraviolet- visual fluorescence.
- ultraviolet- visible light spectral data is combined with MR absorption data.
- the MR data allows measurement of water concentration, and contains specific information about pH, hemoglobin, organic composition, and tissue temperature.
- a MR spectrum of hemoglobin is obtained.
- Hemoglobin is a protein found within erythrocytes and has strong absorbance bands in the visible and MR spectrum.
- Oxy-hemoglobin absorbs at 410 nm, 540 nm, and 580 nm and by taking absorbance measurements at these wavelengths it is possible to deduce total blood volume and oxygenation state.
- Additional physiological information can be obtained by pairing O 2 saturation information with fluorescent spectra specifically including, but not limited to NADH (or NADPH) or ratiometric NADH/FAD data.
- the instant invention provides a method to weight spectral features according to the depth at which they originate, thus providing a depth discriminating feature.
- Depth delineation depth of spectral examination
- the detection of hemoglobin and hence determination of the depth from which the signal has been acquired can be used to trigger the collection of spectral data.
- a pulsatile i.e. relating to pulse or heartbeat
- trending measurement along with each of the aforementioned wavelengths
- the oxygenation state of the tissue can be further derived from the rates of production of bio-molecules such as NADH, NADPH, FAD, and other analytes in the metabolic chain, which may be calculated. Therefore, it can be appreciated that depth discrimination refers to the relative depth normal to the surface of the skin that the preferred analyte signal emanates from.
- the delineation of depth can provide specific information to an algorithm designed for the calculation of analyte concentration. For example, if the concentration of a particular analyte in skin is related to blood flow, the concentration may follow a depth-dependent gradient from the source of the analyte
- the concentration of the analyte at a particular distance from the source can be determined mathematically and an algorithm, with the input of a depth parameter, can adjust the calculated analyte quantity to express that value relative to the depth at which it was sampled.
- the total blood flow can be calculated.
- the oxygenation state of the tissue can be further derived from the rates of production of bio-molecules such as NADH, NADPH, FAD, and other analytes in the metabolic chain, which may be calculated.
- MR and/or Raman generated water information may be correlated with physiological tissue perfusion.
- the MR region contains spectral information from glucose absorption (see Heise refi).
- adjunct data obtained by MR may be used to calibrate and improve the precision of ultraviolet- visible light fluorescence data.
- adjunct MR spectroscopic measurements could improve fluorescence calibrations: 1) by using the water absorbance band in the MR as a means by which to quantitate the amount of water in the tissue (tissue hydration state) and including this information in the fluorescence calibration; and 2) by including spectral regions that contain information about glucose absorbances in tissue directly in the fluorescence calibration.
- the ultraviolet- visible light spectroscopic measurement is combined with at least one adjunct physiological parameter measurement.
- the physiological parameter can be measured via passive measurement techniques or alternatively, actively induced measurement techniques.
- the physiological parameter may be oxygenation, oxygen saturation, temperature, blood volume, blood volume change, blood pressure, blood flow, pulsatile effects, pH, skin perfusion, hydration, vasodilation, nitric oxide (NO), carbon dioxide (CO 2 ), as well as other tissue optical properties, such as contact pressure/optical interface, tissue color, tissue homogeneity, skin roughness, skin stretch, skin tone, ultraviolet effects, ultraviolet dosage, and the like.
- the ultraviolet-visible light spectroscopic measurement is combined with at least one adjunct informational parameter measurement.
- the informational parameter is one or more parameters selected from a group comprising date, time of day, period of time since last meal, content of last meal, drug dosing information such as period of time since last drug administration , dosage of last administration, insulin pump data, age of the patient, skin age of the patient which is the apparent age as determined by build-up of fluorescent AGEs in the skin, skin color, gender, menstrual history, weight, percent body fat, exercise and activity level, pulse rate, type of diabetes, duration of diabetes, type and dosage of non-insulin medications, medical complications secondary to diabetes, pertinent additional medical and family history, aspirin usage, tobacco and/or alcohol usage, and analyte determination category.
- the ultraviolet- visible light spectroscopic measurements are combined with any combination of at least one adjunct physiological parameter measurement, at least one adjunct informational parameter measurement, and at least one adjunct spectroscopic measurement selected from the group comprising infrared, near infrared, ultraviolet and visible light absorbance.
- the ultraviolet- visible light spectroscopic measurements can be performed substantially simultaneously or sequentially with the adjunct measurements. Further, the ultraviolet- visible light spectroscopic measurements and one or more adjunct measurements may be performed at the same or different physical location on the patient.
- adjunct information can be added to fluorescence spectroscopic measurements to improve the ability to quantitate the level of an analyte.
- the adjunctive data provides characteristics of the individual by introducing demographic, physiologic, medical, and other relevant information by the following means:
- Basis set reduction means reducing a set of data down to some more manageable reduced set of variables tlirough the application of some form of algorithm.
- Basis set reduction as a general technique is very common in science (John Stuart Mill, A System of Logic: Ratiocinative and Inductive, variorum edition in Collected Works, vols. 7-8, J.M. Robson, ed.
- pulse rate, blood pressure, blood analyte values measured from a blood sample, height, weight, age, body fat percentage, air temperature, etc.) that was taken either simultaneously or not simultaneously with the fluorescence measurement can simply by concatenated with the fluorescence spectrum prior to multivariate analysis.
- Adjunct measurements can be used as a means of categorizing multivariate calibration models and choosing which one or ones to apply. Multivariate calibration models are only applicable to the set of variables and conditions on which they were modeled. The adjunct measurement can be used as the criteria by which the selection of the most appropriate multivariate calibration model is done.
- adjunct measurement or some reduced basis set form of the adjunct measurement can be used as a direct input into the algorithm or multivariate calibration model being used.
- the adjunct spectral measurement can be used to correct the fluorescence spectrum and remove alterations of the fluorescence spectrum that come from known sources.
- a diffuse reflectance spectrum can be used to correct the fluorescence spectrum for the effects of melanin or hemoglobin absorbances.
- the step of combining primary and adjunct datasets may include aliasing and folding the acquired data, for example, in a Fourier Transfonn spectrometer, for the purpose of making robust quantitative measurements of body constituents non-invasively.
- Fourier- transform spectroscopy (“FTS") provides a set of performance parameters completely different from dispersive spectroscopy. FTS has been widely accepted in the infrared region since 1967, and has all but totally replaced dispersive techniques in the infrared spectroscopy laboratory (H. M. Heise and R. Marbach et al., Noninvasive Blood Glucose Sensors Based on Near-Infrared Spectroscopy, 18(6) Artificial Organs 439-47, 1994, P. R. Griffiths, Fourier Transform Infrared Spectrometry 222(4621) Science 297-
- Aliasing means that the information from two spectrally distinct spectral regions will be combined in one spectrum. This spectrum containing information from both the aliased and non-aliased spectral regions is then input directly into the multivariate calibration model.
- combining comprises using two or more parameters, e.g., parameters, as input variables for one or more algorithms relating to the quantitation of the analyte.
- the invention provides steps of correcting spectroscopic and non-spectroscopic parameters by at least one of the following dimensions: spectral, spatial such as skin depth and skin surface area, and temporal.
- the spatial dimensions may be used to sort out the contributions from pH, electrolytes, temperature, and the like.
- a temperature gradient may exist between the outer surface of the skin and the tissue inside. Accordingly, the effects of temperature on the measured signal may or may not scale with the distance into the tissue normal to the tissue surface whereas contributions from electrolyte concentrations and pH may or may not be more evenly distributed.
- a spatial dimension is used to separate out the effects of temperature on the measured signal from those effects due to pH and electrolyte concentrations.
- Temporal dimensions provide additional selectivity, which can be used to sort out contributions from electrolyte, pulsatile, pressure and temperature changes or contributions from active or passive stimulation. As a result, temporal parameters have particular value when elucidating local and/or systemic responses to varying stimuli.
- Spectral dimensions represent changes in spectral form over time. Therefore, measures of spectral change as a function of time, allow the different variables to be selectively extracted, based upon a temporal dimension.
- the spatial dimension can be utilized to minimize the effects of the temperature gradient on fluorescence or diffuse-reflectance spectra.
- the first step is the derivation of the effects of a temperature gradient on fluorescence spectra and establishing a mathematical model to explain this gradient utilizing an adjunct measurement. It is possible to detect temperature using infrared spectroscopy. h this example, infrared absorption measurements could be used as a mathematical transformation on the fluorescence spectra before the calculative glucose algorithm was applied to them. The algorithm used to calculate glucose concentration would be applied after the transformation and would be made on a spectrum that was independent of temperature gradient effects (as they were accounted for by the adjunct measurement and subsequent transformation).
- Spectral dimensions refer to the change in the shape of spectra over time. Those changes that can be quantified and are not related to analyte concentration can be accounted for in the same manner as the two examples described above with an initial transformation before the application of an algorithm designed to calculate analyte concentration.
- the invention provides a method of signal processing to improve the accessibility of chemically or physically significant information in the analytical signals. Specifically, the intensity values of signals obtained at particular wavelengths can thus be processed to reduce the effect of instrumentation noise and thus processed signals can then be subjected to multivariate analysis using known statistical techniques.
- vibrational spectroscopy for example, infrared or Raman
- vibrational spectroscopy with high specificity and a relatively low signal to noise ratio is utilized to enhance calibration models built with fluorescence spectroscopy data.
- this application is useful when collecting data in a common spectrum on a common frequency axis on the same spectrometer, or alternatively, collecting data with different spectrometers and later combined.
- Calibration refers to the set of operations which establish, under specified conditions, the relationship between values indicated by a measuring instrument or measuring system, and the corresponding standard or known values derived from the standard. It is the process of relating data measurements for the purpose of increasing the accuracy and precision of the methodology and instrumentation in use.
- Statistical calibrations using chemometric methods can be used to extract specific information from a complex set of data.
- relational methods of calibration include linear regression, multiple- linear regression, partial linear regression, and principal components analysis.
- calibrations can be carried out using artificial neural networks, genetic algorithms and rotated principal components analysis.
- the step of calibrating may comprise analyzing the measurements obtained using one or more chemometric techniques, such as multivariate analysis methodologies selected from the group comprising: PLS, PCR, LDA, MLR, LR, LWR, RR, NN, stepwise LR and combinations thereof.
- chemometric techniques such as multivariate analysis methodologies selected from the group comprising: PLS, PCR, LDA, MLR, LR, LWR, RR, NN, stepwise LR and combinations thereof.
- General references for multivariate calibrations include Marten and Naes.
- Instrumentation that detects information for one or more constituents in a complex chemical matrix must rely upon analysis algorithms, such as those derived using chemometrics, in order to reveal information that is specific for one or more chemical constituent.
- Chemometrics techniques can be used to compare unknowns with calibrated standards and databases to provide advanced forms of cluster analysis, and to extract features from an unknown patient that can be used as information in statistical and mathematical models.
- Chemometrics relates to the application of mathematical, statistical and pattern recognition techniques in chemical analysis applications. See, e.g., Brown et al. (1990) Anal. Chem. 62 : 84- 101. Chemometrics is practiced herein in the context of developing and using noninvasive diagnostic instrumentation that employs advanced signal processing and calibration techniques. Signal processing is used to improve the accessibility of physically significant information in analytical signals. Examples of signal processing techniques include Fourier transformation, first and second derivatives, and digital or adaptive filtering.
- PCA Principal components analysis
- chemometric techniques to spectroscopic measurement of chemical analytes in a complex matrix.
- PCA is used to reduce the dimensionality of a large number of interrelated variables while retaining the information that distinguishes one component from another. This reduction is effected using an eigenvector transformation of an original set of interrelated variables (e.g. an absorption spectrum) into a substantially smaller set of uncorrelated principal component (“PC") variables that represents most of the information in the original set.
- PC principal component
- the new set of variables is ordered such that the first few retain most of the variation present in all of the original variables. See, e.g., Jolliffe, L. T., Principal Component Analysis, Sprinter-Verlag, New York (1986).
- each PC is a linear combination of all the original measurement variables.
- the first is a vector in the direction of the greatest variance of the observed variables.
- the succeeding PCs are chosen to represent the greatest variation of the measurement data and to be orthogonal to the previously calculated PC. Therefore, the PCs are arranged in descending order of importance.
- a weighting constant comprises the wavelength coefficients of partial least squares regression and/or principal components regression, or any constant obtained from any statistical calibration that can be used to calculate values (such as analyte concentration) for unknown patients.
- a wavelength weighting factor is an embodiment of a weighting constant which is used in the construction of an optical filter means capable of emphasizing wavelength-specific information from spectral data.
- the wavelength- specific information can be used to determine desired values relating to the patient undergoing analysis (e.g., analyte concentration).
- a wavelength weighting factor can be embodied as a particular filter density (e.g., neutral or wavelength-specific), filter thickness, or the like, such parameters having been determined using the above- described statistical calibration techniques.
- an apparatus for performing the above adjunct methodologies comprises a light source for exciting a target in the tissue with excitation radiation, a detection means for detecting, recording or collecting at least one spectral emission from the excited target, a determining means for determining an adjunct parameter, such as the spectral, physiological, or info ⁇ nation parameters mentioned above, and a means for combining said spectral emission detected with said adjunct parameter to obtain the level of the at least one analyte in the tissue.
- the apparatus comprises a display element, wherein the display element displays the level of one or more analytes and/or the adjunct parameter.
- the apparatus may also comprise a transmitter for transmitting data pertaining to the detected spectral emission, the adjunct parameter, the level of the at least one analyte, or any combination thereof to a centralized server, database, personal computer, or any other electronic receiver desired.
- the apparatus may further include an audio generator that generates one or more sounds notifying the user when analyte level(s) are determined.
- Example 1 Acquire a fluorescence spectrum from a person; acquire a diffuse reflectance (or other adjunct spectral measurement) from the same person, and use the diffuse reflectance spectral measurement as a means by which to determine the appropriate multivariate calibration model to apply to the fluorescence measurement.
- Diffuse reflectance measurements contain information about skin color and skin oxygenation.
- Various multivariate calibration models are based on fluorescence spectra that apply only to specific oxygenation levels or skin colors. The specific multivariate models have smaller errors than general models that apply to all skin colors and oxygenation levels.
- Example 2 Acquire a fluorescence spectrum from a person; acquire a diffuse reflectance spectral measurement (or other adjunct spectral measurement), either aliased into the fluorescence spectrum or non-aliased, then combine the two spectra (concatenate), and use them together in a single multivariate calibration model.
- Example 3 Simultaneously acquire diffuse reflectance spectra and fluorescence spectra. Calculate a skin oxygen saturation value (basis set reduction) from the diffuse reflectance spectrum (using methods like, e.g., Brunelle JA, Degtiarov AM, Moran RF, Race LA.
- a new C * O 2 sat * Api, where A is the analyte value, C is a constant, O sat is the oxygen saturation value obtained from the diffuse reflectance data, and A FI is the fluorescent analyte level. It should be noted that as an alternative, oxygen saturation information may herein be supplied by a pulse oximeter as well.
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Molecular Biology (AREA)
- Animal Behavior & Ethology (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Optics & Photonics (AREA)
- Surgery (AREA)
- Biophysics (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Emergency Medicine (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
Abstract
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
AU2002355272A AU2002355272A1 (en) | 2001-07-25 | 2002-07-24 | Adjunct quantitative system and method for non-invasive measurement of in vivo analytes |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US30738901P | 2001-07-25 | 2001-07-25 | |
US60/307,389 | 2001-07-25 |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2003010510A2 true WO2003010510A2 (fr) | 2003-02-06 |
WO2003010510A3 WO2003010510A3 (fr) | 2004-02-19 |
Family
ID=23189546
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2002/023348 WO2003010510A2 (fr) | 2001-07-25 | 2002-07-24 | Systeme et procede quantitatif d'ajout pour mesure non invasive d'analytes in vivo |
Country Status (2)
Country | Link |
---|---|
AU (1) | AU2002355272A1 (fr) |
WO (1) | WO2003010510A2 (fr) |
Cited By (42)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1522254A1 (fr) * | 2003-10-08 | 2005-04-13 | Hitachi, Ltd. | Appareil de mesure du taux de glycémie |
US6954661B2 (en) | 2003-06-23 | 2005-10-11 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
EP1620708A2 (fr) * | 2003-05-02 | 2006-02-01 | DIRAmed, LLC | Detecteur optique de substance sanguine a analyser corrige a zero |
EP1634061A2 (fr) * | 2003-04-30 | 2006-03-15 | McGILL UNIVERSITY | Methode et systeme pour mesurer la concentration de lactate in vivo |
EP1649803A1 (fr) * | 2004-10-19 | 2006-04-26 | Hitachi Ltd. | Appareil de mesure du taux de sucre sanguin |
US7120478B2 (en) | 2003-07-11 | 2006-10-10 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7215983B2 (en) | 2004-06-30 | 2007-05-08 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7251517B2 (en) | 2004-06-30 | 2007-07-31 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7251515B2 (en) | 2004-02-17 | 2007-07-31 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7251514B2 (en) | 2004-02-26 | 2007-07-31 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7254430B2 (en) | 2003-05-07 | 2007-08-07 | Hitachi, Ltd. | Measuring apparatus for measuring a metabolic characteristic in a human body |
US7254427B2 (en) | 2003-09-24 | 2007-08-07 | Hitachi, Ltd. | Optical measurements apparatus and blood sugar level measuring apparatus using the same |
US7254428B2 (en) | 2004-02-17 | 2007-08-07 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
WO2008039330A1 (fr) * | 2006-09-27 | 2008-04-03 | Nellcor Puritan Bennett Llc | Estimation d'hydratation tissulaire basee sur une mesure de largeur de bande d'absorption spectrale |
US7809418B2 (en) | 2007-10-04 | 2010-10-05 | The Curators Of The University Of Missouri | Optical device components |
WO2011014519A3 (fr) * | 2009-07-29 | 2011-04-28 | Masimo Laboratories, Inc. | Etalonnage de la réflectance des mesures du glucose par fluorescence |
US7961305B2 (en) | 2007-10-23 | 2011-06-14 | The Curators Of The University Of Missouri | Optical device components |
US7961304B2 (en) | 2007-09-13 | 2011-06-14 | The Curators Of The University Of Missouri | Optical device components |
US8175346B2 (en) | 2006-07-19 | 2012-05-08 | Lumidigm, Inc. | Whole-hand multispectral biometric imaging |
US8184873B2 (en) | 2003-04-04 | 2012-05-22 | Lumidigm, Inc. | White-light spectral biometric sensors |
US8229185B2 (en) | 2004-06-01 | 2012-07-24 | Lumidigm, Inc. | Hygienic biometric sensors |
US8229529B2 (en) | 2001-03-16 | 2012-07-24 | Nellcor Puritan Bennett Llc | Device and method for monitoring body fluid and electrolyte disorders |
US8285010B2 (en) | 2007-03-21 | 2012-10-09 | Lumidigm, Inc. | Biometrics based on locally consistent features |
US8340738B2 (en) | 2008-05-22 | 2012-12-25 | The Curators Of The University Of Missouri | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US8355545B2 (en) | 2007-04-10 | 2013-01-15 | Lumidigm, Inc. | Biometric detection using spatial, temporal, and/or spectral techniques |
US8457722B2 (en) | 2001-03-16 | 2013-06-04 | Covidien Lp | Device and method for monitoring body fluid and electrolyte disorders |
US8552359B2 (en) | 2009-04-01 | 2013-10-08 | The Curators of the Univesity of Missouri | Optical spectroscopy device for non-invasive blood glucose detection and associated method of use |
US8570149B2 (en) | 2010-03-16 | 2013-10-29 | Lumidigm, Inc. | Biometric imaging using an optical adaptive interface |
US8731250B2 (en) | 2009-08-26 | 2014-05-20 | Lumidigm, Inc. | Multiplexed biometric imaging |
US8781181B2 (en) | 2006-07-19 | 2014-07-15 | Lumidigm, Inc. | Contactless multispectral biometric capture |
US8787630B2 (en) | 2004-08-11 | 2014-07-22 | Lumidigm, Inc. | Multispectral barcode imaging |
US8945936B2 (en) | 2011-04-06 | 2015-02-03 | Fresenius Medical Care Holdings, Inc. | Measuring chemical properties of a sample fluid in dialysis systems |
US9442065B2 (en) | 2014-09-29 | 2016-09-13 | Zyomed Corp. | Systems and methods for synthesis of zyotons for use in collision computing for noninvasive blood glucose and other measurements |
US9554738B1 (en) | 2016-03-30 | 2017-01-31 | Zyomed Corp. | Spectroscopic tomography systems and methods for noninvasive detection and measurement of analytes using collision computing |
CN107714049A (zh) * | 2017-09-08 | 2018-02-23 | 上海乐糖信息科技有限公司 | 基于多信息融合的无创血糖检测方法、系统以及装置 |
CN109561857A (zh) * | 2016-07-18 | 2019-04-02 | 格鲁科威斯塔公司 | 物质浓度分析方法和设备 |
US10542919B2 (en) | 2008-03-25 | 2020-01-28 | St. Louis Medical Devices, Inc. | Method and system for non-invasive blood glucose detection utilizing spectral data of one or more components other than glucose |
CN111150395A (zh) * | 2020-01-15 | 2020-05-15 | 桂林电子科技大学 | 一种基于生物电阻抗的自适应血糖测量方法 |
US11141083B2 (en) | 2017-11-29 | 2021-10-12 | Samsung Electronics Co., Ltd. | System and method for obtaining blood glucose concentration using temporal independent component analysis (ICA) |
EP3895603A1 (fr) * | 2020-04-14 | 2021-10-20 | Biosensors Beyond Borders Ltd | Dispositif de surveillance |
US20230104416A1 (en) * | 2021-10-01 | 2023-04-06 | Rockley Photonics Limited | Biomarker value calculation method |
CN116889395A (zh) * | 2023-08-24 | 2023-10-17 | 迈德医疗科技(深圳)有限公司 | 一种基于catpca的无创血糖膳食分类方法及系统 |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5665962A (en) * | 1994-04-19 | 1997-09-09 | Fuji Photo Film Co., Ltd. | Image reader and image recorder with interposed photochromic material for reducing flare |
US5985214A (en) * | 1997-05-16 | 1999-11-16 | Aurora Biosciences Corporation | Systems and methods for rapidly identifying useful chemicals in liquid samples |
-
2002
- 2002-07-24 WO PCT/US2002/023348 patent/WO2003010510A2/fr not_active Application Discontinuation
- 2002-07-24 AU AU2002355272A patent/AU2002355272A1/en not_active Abandoned
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5665962A (en) * | 1994-04-19 | 1997-09-09 | Fuji Photo Film Co., Ltd. | Image reader and image recorder with interposed photochromic material for reducing flare |
US5985214A (en) * | 1997-05-16 | 1999-11-16 | Aurora Biosciences Corporation | Systems and methods for rapidly identifying useful chemicals in liquid samples |
Cited By (73)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8457722B2 (en) | 2001-03-16 | 2013-06-04 | Covidien Lp | Device and method for monitoring body fluid and electrolyte disorders |
US8229529B2 (en) | 2001-03-16 | 2012-07-24 | Nellcor Puritan Bennett Llc | Device and method for monitoring body fluid and electrolyte disorders |
US8184873B2 (en) | 2003-04-04 | 2012-05-22 | Lumidigm, Inc. | White-light spectral biometric sensors |
EP1634061A2 (fr) * | 2003-04-30 | 2006-03-15 | McGILL UNIVERSITY | Methode et systeme pour mesurer la concentration de lactate in vivo |
EP1634061A4 (fr) * | 2003-04-30 | 2007-11-21 | Univ Mcgill | Methode et systeme pour mesurer la concentration de lactate in vivo |
EP1620708A2 (fr) * | 2003-05-02 | 2006-02-01 | DIRAmed, LLC | Detecteur optique de substance sanguine a analyser corrige a zero |
EP1620708A4 (fr) * | 2003-05-02 | 2009-04-29 | Diramed Llc | Detecteur optique de substance sanguine a analyser corrige a zero |
US7254430B2 (en) | 2003-05-07 | 2007-08-07 | Hitachi, Ltd. | Measuring apparatus for measuring a metabolic characteristic in a human body |
US7254426B2 (en) | 2003-05-07 | 2007-08-07 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US6954661B2 (en) | 2003-06-23 | 2005-10-11 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7120478B2 (en) | 2003-07-11 | 2006-10-10 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7254427B2 (en) | 2003-09-24 | 2007-08-07 | Hitachi, Ltd. | Optical measurements apparatus and blood sugar level measuring apparatus using the same |
US7156810B2 (en) | 2003-10-08 | 2007-01-02 | Hitachi, Ltd. | Blood sugar level measuring method and apparatus |
EP1522254A1 (fr) * | 2003-10-08 | 2005-04-13 | Hitachi, Ltd. | Appareil de mesure du taux de glycémie |
US7251515B2 (en) | 2004-02-17 | 2007-07-31 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7254428B2 (en) | 2004-02-17 | 2007-08-07 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7251514B2 (en) | 2004-02-26 | 2007-07-31 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US8229185B2 (en) | 2004-06-01 | 2012-07-24 | Lumidigm, Inc. | Hygienic biometric sensors |
US7251517B2 (en) | 2004-06-30 | 2007-07-31 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US7215983B2 (en) | 2004-06-30 | 2007-05-08 | Hitachi, Ltd. | Blood sugar level measuring apparatus |
US8787630B2 (en) | 2004-08-11 | 2014-07-22 | Lumidigm, Inc. | Multispectral barcode imaging |
EP1649803A1 (fr) * | 2004-10-19 | 2006-04-26 | Hitachi Ltd. | Appareil de mesure du taux de sucre sanguin |
US8781181B2 (en) | 2006-07-19 | 2014-07-15 | Lumidigm, Inc. | Contactless multispectral biometric capture |
US8175346B2 (en) | 2006-07-19 | 2012-05-08 | Lumidigm, Inc. | Whole-hand multispectral biometric imaging |
US8831297B2 (en) | 2006-07-19 | 2014-09-09 | Lumidigm, Inc. | Contactless multispectral biometric capture |
WO2008039330A1 (fr) * | 2006-09-27 | 2008-04-03 | Nellcor Puritan Bennett Llc | Estimation d'hydratation tissulaire basee sur une mesure de largeur de bande d'absorption spectrale |
US8285010B2 (en) | 2007-03-21 | 2012-10-09 | Lumidigm, Inc. | Biometrics based on locally consistent features |
US8355545B2 (en) | 2007-04-10 | 2013-01-15 | Lumidigm, Inc. | Biometric detection using spatial, temporal, and/or spectral techniques |
US7961304B2 (en) | 2007-09-13 | 2011-06-14 | The Curators Of The University Of Missouri | Optical device components |
US7809418B2 (en) | 2007-10-04 | 2010-10-05 | The Curators Of The University Of Missouri | Optical device components |
US7961305B2 (en) | 2007-10-23 | 2011-06-14 | The Curators Of The University Of Missouri | Optical device components |
US11147482B2 (en) | 2008-03-25 | 2021-10-19 | St. Louis Medical Devices, Inc. | Method and system for non-invasive blood glucose measurement using signal change of the non-glucose components induced by the presence of glucose |
US10542919B2 (en) | 2008-03-25 | 2020-01-28 | St. Louis Medical Devices, Inc. | Method and system for non-invasive blood glucose detection utilizing spectral data of one or more components other than glucose |
US10080515B2 (en) | 2008-05-22 | 2018-09-25 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US11076781B2 (en) | 2008-05-22 | 2021-08-03 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US12036019B2 (en) | 2008-05-22 | 2024-07-16 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US11986291B2 (en) | 2008-05-22 | 2024-05-21 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US11553859B2 (en) | 2008-05-22 | 2023-01-17 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US10973442B2 (en) | 2008-05-22 | 2021-04-13 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US10959650B2 (en) | 2008-05-22 | 2021-03-30 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US8340738B2 (en) | 2008-05-22 | 2012-12-25 | The Curators Of The University Of Missouri | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US10070809B2 (en) | 2008-05-22 | 2018-09-11 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US9877670B2 (en) | 2008-05-22 | 2018-01-30 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US9814415B2 (en) | 2008-05-22 | 2017-11-14 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US9788764B2 (en) | 2008-05-22 | 2017-10-17 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US9629576B2 (en) | 2008-05-22 | 2017-04-25 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US9566024B2 (en) | 2008-05-22 | 2017-02-14 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US9579049B2 (en) | 2008-05-22 | 2017-02-28 | St. Louis Medical Devices, Inc. | Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis |
US8552359B2 (en) | 2009-04-01 | 2013-10-08 | The Curators of the Univesity of Missouri | Optical spectroscopy device for non-invasive blood glucose detection and associated method of use |
WO2011014519A3 (fr) * | 2009-07-29 | 2011-04-28 | Masimo Laboratories, Inc. | Etalonnage de la réflectance des mesures du glucose par fluorescence |
US8872908B2 (en) | 2009-08-26 | 2014-10-28 | Lumidigm, Inc | Dual-imager biometric sensor |
US8731250B2 (en) | 2009-08-26 | 2014-05-20 | Lumidigm, Inc. | Multiplexed biometric imaging |
US8570149B2 (en) | 2010-03-16 | 2013-10-29 | Lumidigm, Inc. | Biometric imaging using an optical adaptive interface |
US8945936B2 (en) | 2011-04-06 | 2015-02-03 | Fresenius Medical Care Holdings, Inc. | Measuring chemical properties of a sample fluid in dialysis systems |
US9453794B2 (en) | 2014-09-29 | 2016-09-27 | Zyomed Corp. | Systems and methods for blood glucose and other analyte detection and measurement using collision computing |
US9459202B2 (en) | 2014-09-29 | 2016-10-04 | Zyomed Corp. | Systems and methods for collision computing for detection and noninvasive measurement of blood glucose and other substances and events |
US9459203B2 (en) | 2014-09-29 | 2016-10-04 | Zyomed, Corp. | Systems and methods for generating and using projector curve sets for universal calibration for noninvasive blood glucose and other measurements |
US9448165B2 (en) | 2014-09-29 | 2016-09-20 | Zyomed Corp. | Systems and methods for control of illumination or radiation collection for blood glucose and other analyte detection and measurement using collision computing |
US9459201B2 (en) | 2014-09-29 | 2016-10-04 | Zyomed Corp. | Systems and methods for noninvasive blood glucose and other analyte detection and measurement using collision computing |
US9448164B2 (en) | 2014-09-29 | 2016-09-20 | Zyomed Corp. | Systems and methods for noninvasive blood glucose and other analyte detection and measurement using collision computing |
US9442065B2 (en) | 2014-09-29 | 2016-09-13 | Zyomed Corp. | Systems and methods for synthesis of zyotons for use in collision computing for noninvasive blood glucose and other measurements |
US9610018B2 (en) | 2014-09-29 | 2017-04-04 | Zyomed Corp. | Systems and methods for measurement of heart rate and other heart-related characteristics from photoplethysmographic (PPG) signals using collision computing |
US9554738B1 (en) | 2016-03-30 | 2017-01-31 | Zyomed Corp. | Spectroscopic tomography systems and methods for noninvasive detection and measurement of analytes using collision computing |
CN109561857B (zh) * | 2016-07-18 | 2022-05-17 | 格鲁科威斯塔公司 | 物质浓度分析设备 |
CN109561857A (zh) * | 2016-07-18 | 2019-04-02 | 格鲁科威斯塔公司 | 物质浓度分析方法和设备 |
CN107714049A (zh) * | 2017-09-08 | 2018-02-23 | 上海乐糖信息科技有限公司 | 基于多信息融合的无创血糖检测方法、系统以及装置 |
US11141083B2 (en) | 2017-11-29 | 2021-10-12 | Samsung Electronics Co., Ltd. | System and method for obtaining blood glucose concentration using temporal independent component analysis (ICA) |
CN111150395A (zh) * | 2020-01-15 | 2020-05-15 | 桂林电子科技大学 | 一种基于生物电阻抗的自适应血糖测量方法 |
EP3895603A1 (fr) * | 2020-04-14 | 2021-10-20 | Biosensors Beyond Borders Ltd | Dispositif de surveillance |
US20230104416A1 (en) * | 2021-10-01 | 2023-04-06 | Rockley Photonics Limited | Biomarker value calculation method |
WO2023052843A1 (fr) * | 2021-10-01 | 2023-04-06 | Rockley Photonics Limited | Méthode de calcul de valeur de biomarqueur |
CN116889395A (zh) * | 2023-08-24 | 2023-10-17 | 迈德医疗科技(深圳)有限公司 | 一种基于catpca的无创血糖膳食分类方法及系统 |
CN116889395B (zh) * | 2023-08-24 | 2024-02-13 | 迈德医疗科技(深圳)有限公司 | 一种基于catpca的无创血糖膳食分类方法及系统 |
Also Published As
Publication number | Publication date |
---|---|
WO2003010510A3 (fr) | 2004-02-19 |
AU2002355272A1 (en) | 2003-02-17 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2003010510A2 (fr) | Systeme et procede quantitatif d'ajout pour mesure non invasive d'analytes in vivo | |
Delbeck et al. | Non-invasive monitoring of blood glucose using optical methods for skin spectroscopy—Opportunities and recent advances | |
US20140330098A1 (en) | Reflectance calibration of fluorescence-based glucose measurements | |
EP1467652B1 (fr) | Mesure indirecte d'analytes tissulaires par l'intermediaire de proprietes tissulaires | |
Heise et al. | Noninvasive blood glucose sensors based on near‐infrared spectroscopy | |
US5377674A (en) | Method for non-invasive and in-vitro hemoglobin concentration measurement | |
US7027848B2 (en) | Apparatus and method for non-invasive spectroscopic measurement of analytes in tissue using a matched reference analyte | |
CN108024727B (zh) | 生物传感器 | |
US8406839B2 (en) | Method and apparatus for determining blood analytes | |
US7725144B2 (en) | Determination of disease state using raman spectroscopy of tissue | |
US20050209515A1 (en) | Method and apparatus for presentation of noninvasive glucose concentration information | |
TW200305019A (en) | Method and apparatus using alternative site glucose determinations to calibrate and maintain noninvasive and implantable analyzers | |
US6958039B2 (en) | Method and instruments for non-invasive analyte measurement | |
WO2004081524A2 (fr) | Procede de pretraitement de donnees selon les sites de mesure pour etalonnage et prediction robustes | |
JP2008132335A (ja) | 組織の光学特性によるグルコースの非浸襲的測定 | |
Heise et al. | Near-infrared reflectance spectroscopy for noninvasive monitoring of metabolites | |
Heise | Medical applications of NIR spectroscopy | |
Poddar et al. | Non-invasive glucose monitoring techniques: A review and current trends | |
Liu et al. | Next step of non-invasive glucose monitor by NIR technique from the well controlled measuring condition and results | |
Bai | Noninvasive near infrared spectroscopy on living tissue with multivariate calibration approaches | |
Nooshnab et al. | A Review of Minimally and Non-invasive Glucose Monitoring Techniques, Devices and Sensors | |
EP3906848A1 (fr) | Système et procédé de dépistage d'infection | |
Vashist et al. | Non-invasive analytics for point-of-care testing of glucose | |
Mohanram et al. | Measurement of blood glucose using non-invasive methods–a review | |
Manjukiran et al. | Non Invasive Blood Glucose Level Detection |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A2 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BY BZ CA CH CN CO CR CU CZ DE DK DM DZ EC EE ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NO NZ PL PT RO RU SD SE SG SI SK SL TJ TM TR TT TZ UA UG US UZ VN YU ZA ZW Kind code of ref document: A2 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BY BZ CA CH CN CO CR CU CZ DE DM DZ EC EE ES FI GB GD GE GH HR HU ID IL IN IS JP KE KG KP KR LC LK LR LS LT LU LV MA MD MG MN MW MX MZ NO NZ PL PT RO RU SE SG SI SK SL TJ TM TR TT TZ UA US UZ VN YU ZA |
|
AL | Designated countries for regional patents |
Kind code of ref document: A2 Designated state(s): GH GM KE LS MW MZ SD SL SZ UG ZM ZW AM AZ BY KG KZ RU TJ TM AT BE BG CH CY CZ DK EE ES FI FR GB GR IE IT LU MC PT SE SK TR BF BJ CF CG CI GA GN GQ GW ML MR NE SN TD TG Kind code of ref document: A2 Designated state(s): GH GM KE LS MW MZ SD SL SZ TZ UG ZM ZW AM AZ BY KG KZ MD RU TJ TM AT BE BG CH CY CZ DE DK EE ES FI FR GB GR IE IT LU MC NL PT SE SK TR BF BJ CF CG CI CM GA GN GQ GW ML MR NE SN TD TG |
|
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
DFPE | Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101) | ||
REG | Reference to national code |
Ref country code: DE Ref legal event code: 8642 |
|
122 | Ep: pct application non-entry in european phase | ||
NENP | Non-entry into the national phase in: |
Ref country code: JP |
|
WWW | Wipo information: withdrawn in national office |
Country of ref document: JP |