EP4121760A1 - Systèmes et méthodes pour la détermination non invasive de l'infection par le coronavirus covid-19 - Google Patents

Systèmes et méthodes pour la détermination non invasive de l'infection par le coronavirus covid-19

Info

Publication number
EP4121760A1
EP4121760A1 EP21771884.0A EP21771884A EP4121760A1 EP 4121760 A1 EP4121760 A1 EP 4121760A1 EP 21771884 A EP21771884 A EP 21771884A EP 4121760 A1 EP4121760 A1 EP 4121760A1
Authority
EP
European Patent Office
Prior art keywords
membrane
virus
sampler
collected media
individuals
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP21771884.0A
Other languages
German (de)
English (en)
Other versions
EP4121760A4 (fr
Inventor
Eran Gabbai
Yaniv Maydar
Regina AHARONOV-NADBORNY
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Terahertz Group Ltd
Original Assignee
Terahertz Group Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from IL273709A external-priority patent/IL273709A/en
Application filed by Terahertz Group Ltd filed Critical Terahertz Group Ltd
Publication of EP4121760A1 publication Critical patent/EP4121760A1/fr
Publication of EP4121760A4 publication Critical patent/EP4121760A4/fr
Pending legal-status Critical Current

Links

Classifications

    • 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
    • G01N21/552—Attenuated total reflection
    • G01N21/553—Attenuated total reflection and using surface plasmons
    • 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
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/3581—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using far infrared light; using Terahertz radiation
    • 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
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G01N33/497—Physical analysis of biological material of gaseous biological material, e.g. breath
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • 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
    • G01N21/75—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated
    • G01N21/77—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator
    • G01N2021/775—Indicator and selective membrane
    • 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
    • G01N2201/12—Circuits of general importance; Signal processing
    • G01N2201/129—Using chemometrical methods
    • G01N2201/1296—Using chemometrical methods using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods

Definitions

  • the present disclosure relates to systems and methods for non-invasively determination of whether individuals are infected by the COVID-19 coronavirus, and in particular, the presence or absence of COVID-19.
  • Coronaviruses are a large family of viruses that cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV).
  • MERS-CoV Middle East Respiratory Syndrome
  • SARS-CoV Severe Acute Respiratory Syndrome
  • Coronavirus disease (COVID-19) is a new strain that was discovered in 2019 and has not been previously identified in individuals.
  • Coronaviruses are zoonotic, meaning they are transmitted between animals and people. Detailed investigations found that SARS-CoV was transmitted from civet cats to humans and MERS-CoV from dromedary camels to humans. Several known coronaviruses are circulating in animals that have not yet infected humans.
  • Standard recommendations to prevent infection spread include regular hand washing, covering mouth and nose when coughing and sneezing, thoroughly cooking meat and eggs. Avoid close contact with anyone showing symptoms of respiratory illness such as coughing and sneezing. Until now no quick, label free, nondestructive method of identifying and distinguishing between a healthy human from an infected one has been presented.
  • said signature is information indicative of said virus; said information being selected from a group consisting of cell unit of said virus, viral proteins, cellular debris, debris of said virus, hydrates of said virus, hydrates of debris of said virus, hydrates of the 3D structure of said virus and a cell, aggregates of said virus, cytokines, increased level of interleukin (IL)-2, interleukin IL-7, interleukin-2 receptor (IL-2R), interleukin-6 (IL-6), granulocytecolony, stimulating factor, interferon-g, inducible protein 10, monocyte chemoattractant, protein 1, macrophage, inflammatory protein 1-a, and tumor necrosis factor-a, and any combination thereof.
  • IL interleukin
  • IL-7 interleukin-2 receptor
  • IL-6 interleukin-6
  • SSPPs spoof surface plasmon polaritons
  • said virus is selected from a group selected from COV viruses family, COVID- 19, Influenza, Avian influenza and any combination thereof.
  • said electromagnetic testing unit comprising at least one electromagnetic radiation transmitter and at least one electromagnetic radiation detector.
  • control unit is configured and operable for performing a pattern recognition of said signature.
  • control unit trains a machine learning model to detect at least one parameter in the absorption spectrum of said membrane with said collected volatile compounds and/or aerosols being scanned with an electromagnetic radiation in the THz range of a plurality of membrane stored in said communicable and readable database in order to generate information data being indicative of said virus free individuals.
  • control unit trains a machine learning model to detect at least one parameter in the absorption spectrum of said membrane with said collected volatile compounds and/or aerosols being scanned with an electromagnetic radiation in the THz range of a plurality of membrane stored in said communicable and readable database in order to generate information data being indicative of said virus infected individuals.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit detects said signature the absorption spectrum of said membrane with said VCs and/or aerosols being indicative of at least one said virus free individuals by means of said trained machine learning model.
  • control unit detects said signature the absorption spectrum of said membrane with said VCs and/or aerosols being indicative of at least one said virus infected individuals by means of said trained machine learning model.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit performs at least one algorithm selected from a group consisting of Leave One Out (LOO) algorithm, Principal Component Analysis algorithm, k-nearest neighbors algorithm, Quadrature, Fisher's linear discriminant, Fisher's nonlinear discriminant, Network Acceleration algorithm (NNA), any machine learning algorithm and any combination thereof in order to generate information data being indicative of said virus infected individuals.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus free or virus infected individuals.
  • CH4 Water vapor Methane
  • C02 Carbon dioxide
  • Nitrous oxide N20
  • Ozone 03
  • Chlorofluorocarbons CFCs
  • Hydrofluorocarbons includes HCFCs and HFCs
  • NO N02 and any combination thereof.
  • CH4 Water vapor Methane
  • C02 Carbon dioxide
  • Nitrous oxide N20
  • Ozone 03
  • Chlorofluorocarbons CFCs
  • Hydrofluorocarbons includes HCFCs and HFCs
  • NO N02 and any combination thereof.
  • a radiation transmitter unit being configured and operable to scan said membrane holding the collected volatile compounds and/or aerosols by generating an electromagnetic radiation in the range of THz within a scanning window of about 100 GHz
  • a detection unit being configured and operable to detect an electromagnetic radiation emitted by said collected volatile compounds and/or aerosols.
  • said signature is information indicative of said virus; said information being selected from a group consisting of cell unit of said virus, viral proteins, cellular debris, debris of said virus, hydrates of said virus, hydrates of debris of said virus, hydrates of the 3D structure of said virus and a cell, aggregates of said virus, cytokines, increased level of interleukin (IL)-2, interleukin IL-7, interleukin-2 receptor (IL-2R), interleukin-6 (IL-6), granulocytecolony, stimulating factor, interferon-g, inducible protein 10, monocyte chemoattractant, protein 1, macrophage, inflammatory protein 1-a, and tumor necrosis factor-a, and any combination thereof.
  • IL interleukin
  • IL-7 interleukin-2 receptor
  • IL-6 interleukin-6
  • SSPPs spoof surface plasmon polaritons
  • said sampler is at least one selected from a group consisting of a breathalyzer, a straw-like device, any handheld device, any IOT device into which human breath is exhaled.
  • control unit is configured and operable for performing a pattern recognition of said signature.
  • system additionally comprising at one communicable and readable database; said database comprising collected volatile compounds and/or aerosols being scanned with an electromagnetic radiation in the THz range.
  • control unit trains a machine learning model to detect at least one parameter in the absorption spectrum of said membrane with said collected volatile compounds and/or aerosols being scanned with an electromagnetic radiation in the THz range of a plurality of membrane stored in said communicable and readable database in order to generate information data being indicative of said virus free individuals.
  • control unit is configured and operable for performing a pattern recognition of said signature.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit detects said signature the absorption spectrum of said membrane with said VCs and/or aerosols being indicative of at least one said virus free individuals by means of said trained machine learning model.
  • said control unit detects said signature the absorption spectrum of said membrane with said VCs and/or aerosols being indicative of at least one said virus infected individual by means of said trained machine learning model.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit performs at least one algorithm selected from a group consisting of Leave One Out (LOO) algorithm, Principal Component Analysis algorithm, k-nearest neighbors algorithm, Quadrature, Fisher's linear discriminant, Fisher's nonlinear discriminant, Network Acceleration algorithm (NNA), any machine learning algorithm and any combination thereof in order to generate information data being indicative of said virus infected individuals.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus free individuals.
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus infected individuals.
  • volatile compounds and/or aerosols comprise at least one selected from a group consisting of organic compound, inorganic compound, mixture thereof, Ketones, aromatic alcohols, aldehydes, 1 -butanol, dimethyl disulfide, methyl benzene, hexanal, phenylethane, heptanal, benzaldehyde, dimethyl trisulfide, phenol, 2-(2- ethoxyethoxy)ethanol, 2-ethyl- 1 -hexanol, 5 -isopropeny 1- 1 -methyl- 1 cyclohexene, acetophenone, 2-nonanone, 2-decanone, 2-isopropylphenol, benzothiazole, 2-undecanone, 1,3-diacetylbenzene, diethyl phthalate, 1,3-diphenyl propane, Ammonia, Greenhouse gases selected from
  • a radiation transmitter unit being configured and operable to scan said membrane holding the collected volatile compounds and/or aerosols by generating an electromagnetic radiation in the range of THz within a scanning window of about 100 GHz
  • a detection unit being configured and operable to detect an electromagnetic radiation emitted by said collected volatile compounds and/or aerosols.
  • IL interleukin
  • IL-6 interleukin-6
  • aid parameter selected from a group consisting of, trends in said database of said at least one tested individuals, eigenvector of said database of said at least one tested individuals,
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus free individuals.
  • a radiation transmitter unit being configured and operable to scan said membrane holding the collected volatile compounds and/or aerosols by generating an electromagnetic radiation in the range of THz within a scanning window of about 100 GHz
  • a detection unit being configured and operable to detect an electromagnetic radiation emitted by said collected volatile compounds and/or aerosols.
  • said signature is information indicative of said virus; said information being selected from a group consisting of cell unit of said virus, viral proteins, cellular debris, debris of said virus, hydrates of said virus, hydrates of debris of said virus, hydrates of the 3D structure of said virus and a cell, aggregates of said virus, cytokines, increased level of interleukin (IL)-2, interleukin IL-7, interleukin-2 receptor (IL-2R), interleukin-6 (IL-6), granulocytecolony, stimulating factor, interferon-g, inducible protein 10, monocyte chemoattractant, protein 1, macrophage, inflammatory protein 1-a, and tumor necrosis factor-a, and any combination thereof.
  • IL interleukin
  • IL-7 interleukin-2 receptor
  • IL-6 interleukin-6
  • SSPPs spoof surface plasmon polaritons
  • control unit trains a machine learning model to detect at least one parameter in the absorption spectrum of said membrane with said collected volatile compounds and/or aerosols being scanned with an electromagnetic radiation in the THz range of a plurality of membrane stored in said communicable and readable database in order to generate information data being indicative of said virus free individuals.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus free individuals.
  • said signature is information indicative of said virus; said information being selected from a group consisting of cell unit of said virus, viral proteins, cellular debris, debris of said virus, hydrates of said virus, hydrates of debris of said virus, hydrates of the 3D structure of said virus and a cell, aggregates of said virus, cytokines, increased level of interleukin (IL)-2, interleukin IL-7, interleukin-2 receptor (IL-2R), interleukin-6 (IL-6), granulocytecolony, stimulating factor, interferon-g, inducible protein 10, monocyte chemoattractant, protein 174, macrophage, inflammatory protein 1-a, and tumor necrosis factor-a, and any combination thereof.
  • IL interleukin
  • IL-7 interleukin-2 receptor
  • IL-6 interleukin-6
  • SSPPs spoof surface plasmon polaritons
  • said sampler is at least one selected from a group consisting of a breathalyzer, a straw-like device, any handheld device, any IOT device into which human breath is exhaled.
  • control unit is configured and operable for performing a pattern recognition of said signature.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Past Fourier Transformation in order to generate information data being indicative of said virus free individuals.
  • CH4 Water vapor Methane
  • C02 Carbon dioxide
  • SSPPs surface plasmon polaritons
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus free individuals.
  • a radiation transmitter unit being configured and operable to scan said membrane holding the collected volatile compounds and/or aerosols by generating an electromagnetic radiation in the range of THz within a scanning window of about 100 GHz
  • a detection unit being configured and operable to detect an electromagnetic radiation emitted by said collected volatile compounds and/or aerosols.
  • FIG. lb schematically illustrates the exemplary embodiment of Fig. la.
  • FIG. lc schematically illustrates the exemplary embodiment of Fig. la.
  • FIG. Id schematically illustrates the exemplary embodiment of Fig. la.
  • FIG. le schematically illustrates the exemplary embodiment of Fig. la.
  • FIG. If schematically illustrates the exemplary embodiment of Fig. la.
  • FIG. lg schematically illustrates the exemplary embodiment of Fig. la.
  • FIG. 2a schematically illustrates an exemplary membrane according to an embodiment.
  • FIG. 2b schematically illustrates a membrane according to an exemplary embodiment.
  • FIG. 3a schematically illustrates an electromagnetic testing unit (tester) according to an exemplary embodiment.
  • Fig. 3b depicts a process according to an exemplary embodiment.
  • Fig. 3c depicts a process according to an exemplary embodiment.
  • Fig. 3d depicts a process according to an exemplary embodiment.
  • Fig. 3e depicts a process according to an exemplary embodiment.
  • Fig. 3f depicts a process according to an exemplary embodiment.
  • Fig. 3g depicts a process according to an exemplary embodiment.
  • Fig. 3h depicts a process according to an exemplary embodiment.
  • Fig. 3i depicts a process according to an exemplary embodiment.
  • Fig. 3j depicts a process according to an exemplary embodiment.
  • Fig. 3k depicts a process according to an exemplary embodiment.
  • Fig. 31 depicts a process according to an exemplary embodiment.
  • Fig. 3m depicts a process according to an exemplary embodiment.
  • Fig. 3n depicts a process according to an exemplary embodiment.
  • FIG. 4a schematically illustrates another exemplary embodiment of the sampler.
  • FIG. 4b schematically illustrates another exemplary embodiment of the sampler.
  • Fig. 4c schematically illustrates another exemplary embodiment of the sampler.
  • Fig. 4d schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • FIG. 5a schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 5b schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 5c schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 5d schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 5e schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 5f schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 5g schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 5h schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 5i schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • FIG. 6a schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6b schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6c schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6d schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6e schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6f schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6g schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6h schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6i schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • FIG. 6j schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6k schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 61 schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6m schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6n schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6o schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6p schematically illustrates another exemplary embodiment of the sampler and/or method of sampling with the same.
  • Fig. 6q depicts a representative control arrangement according to an embodiment.
  • Fig. 7 depicts a component according to an embodiment.
  • Fig. 8a illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8b illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8c illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8d illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8e illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8f illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8g illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8h illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8i illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8j illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • Fig. 8k illustrates the spectrum analysis received from the THz scan of the volatile compounds and/or aerosols captured in the membrane.
  • FIG. 9a illustrates a schematic of a sampler according to an exemplary embodiment.
  • Fig. 9b illustrates performance of the sampler.
  • Fig. 9c illustrates performance of the sampler.
  • Fig. 9d illustrates performance of the sampler.
  • Fig. 9e illustrates performance of the sampler.
  • Fig. 9f illustrates performance of the sampler.
  • Fig. 9g illustrates performance of the sampler.
  • Fig. 9h illustrates performance of the sampler.
  • Fig. 9i illustrates performance of the sampler.
  • Fig. 9j illustrates performance of the sampler.
  • Fig. 9k illustrates performance of the sampler.
  • Fig. 91 illustrates performance of the sampler.
  • Fig. 9m illustrates performance of the sampler.
  • Fig. 9n illustrates contour plots of the sampler performance.
  • Fig. 9o illustrates performance of the sampler.
  • Fig. 9p illustrates performance of the sampler.
  • Fig. 9q illustrates contour plots of the sampler performance.
  • Fig. 9r illustrates performance of the sampler.
  • Fig. 9s illustrates performance of the sampler.
  • Fig. 9t illustrates contour plots of the sampler performance.
  • any reference in the specification to a method should be applied mutatis mutandis to a system capable of executing the method. Conversely, any reference in the specification to a system should be applied mutatis mutandis to a method that may be executed by the system.
  • the term “healthy individual” refers hereinafter to a CoV free individual (namely COVID-19 free individual) and/or recovered Cov individual (namely COVTD-19 recovered individual).
  • CoV Coronaviruses
  • MERS-CoV Middle East Respiratory Syndrome
  • SARS- CoV Severe Acute Respiratory Syndrome
  • COVTD-19 Coronavirus disease
  • Coronaviruses are zoonotic, meaning they are transmitted between animals and people. Detailed investigations found that SARS-CoV was transmitted from civet cats to humans and MERS-CoV from dromedary camels to humans. Several known coronaviruses are circulating in animals that have not yet infected humans. [0404] Common signs of infection include respiratory symptoms, fever, cough, shortness of breath and breathing difficulties. In more severe cases, infection can cause pneumonia, severe acute respiratory syndrome, kidney failure and even death.
  • Standard recommendations to prevent infection spread include regular hand washing, covering mouth and nose when coughing and sneezing, thoroughly cooking meat and eggs, and avoiding close contact with anyone showing symptoms of respiratory illness such as coughing and sneezing.
  • band-stop filter or “band-rejection filter” refers hereinafter to a filter that passes most frequencies unaltered, but attenuates those in a specific range to very low levels. It is the opposite of a band-pass filter.
  • a notch filter is a band-stop filter with a narrow stopband.
  • a notch Filter is also known as a Band Stop filter or Band Reject Filter. These filters reject/attenuate signals in a specific frequency band called the stop band frequency range and pass the signals above and below this band. For example, if a Notch Filter has a stop band frequency from 1500 MHz to 1550 MHz, it will pass all signals from DC to 1500 MHz and above 1550 MHz. It will only block those signals from 1500 MHz to 1550 MHz.
  • debris refers hereinafter to organic waste left over after a cell dies by undergoing apoptosis or lysis.
  • the term “Influenza” or "the flu”, is an infectious disease caused by an influenza virus.
  • Type D has not been known to infect humans, but is believed to have the potential to do so.
  • the virus is spread through the air from coughs or sneezes. This is believed to occur mostly over relatively short distances. It can also be spread by touching surfaces contaminated by the virus and then touching the eyes, nose, or mouth.
  • a person may be infectious to others both before and during the time they are showing symptoms.
  • the infection may be confirmed by testing the throat, sputum, or nose for the virus. A number of rapid tests are available; however, people may still have the infection even if the results are negative.
  • a type of polymerase chain reaction that detects the virus's RNA is more accurate.
  • Influenza symptoms are a mixture of symptoms of common cold and pneumonia, body ache, headache, and fatigue. Diarrhea is not usually a symptom of influenza in adults, although it has been seen in some human cases of the H5N1 "bird flu" and can be a symptom in children. The symptoms most reliably seen in influenza are shown in the adjacent table.
  • influenza refers hereinafter to a variety of influenza caused by viruses adapted to birds.
  • the term “common cold” or “cold” refers hereinafter to a viral infectious disease of the upper respiratory tract that primarily affects the nose. The throat, sinuses, and larynx may also be affected. Well over 200 virus strains are implicated in causing the common cold, with rhinoviruses being the most common. They spread through the air during close contact with infected people or indirectly through contact with objects in the environment, followed by transfer to the mouth or nose. There is no vaccine for the common cold. The primary methods of prevention are handwashing; not touching the eyes, nose or mouth with unwashed hands; and staying away from sick people.
  • viral protein refers herein to both a component and a product of a virus.
  • Viral proteins are grouped according to their functions, and groups of viral proteins include structural proteins, nonstructural proteins, regulatory, and accessory proteins. Viruses are non-living and they do not have the means to reproduce on their own. They depend on their host cell's metabolism for energy, enzymes, and precursors, in order to reproduce. Thus, viruses do not code for many of their own viral proteins, and instead use the host cell's machinery to produce the viral proteins they require for replication.
  • Cytokines refers herein to a broad and loose category of small proteins (-5-20 kDa) important in cell signaling. Cytokines are peptides, and cannot cross the lipid bilayer of cells to enter the cytoplasm. Cytokines have been shown to be involved in autocrine, paracrine and endocrine signaling as immunomodulating agents. Their definite distinction from hormones is still part of ongoing research. Cytokines include chemokines, interferons, interleukins, lymphokines, and tumor necrosis factors, but generally not hormones or growth factors (despite some overlap in the terminology).
  • Cytokines are produced by a broad range of cells, including immune cells like macrophages, B lymphocytes, T lymphocytes and mast cells, as well as endothelial cells, fibroblasts, and various stromal cells; a given cytokine may be produced by more than one type of cell.
  • cytokines act through receptors, and are especially important in the immune system; cytokines modulate the balance between humoral and cell-based immune responses, and they regulate the maturation, growth, and responsiveness of particular cell populations. Some cytokines enhance or inhibit the action of other cytokines in complex ways.
  • Cytokines storms may have been the cause of severe adverse events during a clinical trial of TGN1412.
  • Cytokine storms are also suspected to be the main cause of death in the 1918 "Spanish Flu” pandemic. Deaths were weighted more heavily towards people with healthy immune systems, due to their ability to produce stronger immune responses, with dramatic increases in cytokine levels.
  • hypocytokinemia refers herein to a potentially fatal immune reaction consisting of a positive feedback loop between cytokines and immune cells, with highly elevated levels of various cytokines.
  • Cytokine release syndrome or “cytokine storm syndrome (CSS)” refers herein to a form of systemic inflammatory response syndrome (SIRS) that can be triggered by a variety of factors such as infections and certain drugs. It occurs when large numbers of white blood cells are activated and release inflammatory cytokines, which in turn activate yet more white blood cells. CRS is also an adverse effect of some monoclonal antibody drugs, as well as adoptive T-cell therapies. Severe cases have been called cytokine storms.
  • SIRS systemic inflammatory response syndrome
  • GVHD graft-versus-host disease
  • CO VTD- 19 coronavirus disease 2019
  • ARDS acute respiratory distress syndrome
  • sepsis sepsis
  • Ebola avian influenza
  • smallpox smallpox
  • SIRS systemic inflammatory response syndrome
  • SARS-CoV-2 severe acute respiratory syndrome coronavirus 2
  • SARS-CoV-2 severe acute respiratory syndrome coronavirus 2
  • This systemic hyperinflammation results in inflammatory lymphocytic and monocytic infiltration of the lung and the heart, causing ARDS and cardiac failure.
  • Patients with fulminant COVTD-19 and ARDS have classical serum biomarkers of CRS including elevated CRP, LDH, IL-6, and ferritin.
  • PCR Polymerase chain reaction
  • PCR Ct refers hereinafter to the PCR cycle number at which the sample’s reaction curve intersects the threshold line. This value tells how many cycles it took to detect a real signal from the samples. Real-Time PCR runs will have a reaction curve for each sample, and therefore many Ct values. Ct values are inverse to the amount of target nucleic acid that is in the sample, and correlate to the number of target copies in the sample. Lower Ct values (e.g., below 34 cycles) indicate high amounts of target sequence. Higher Ct values (above 34 cycles) mean lower amounts of the target nucleic acid.
  • humidity refers hereinafter to the concentration of water vapor present in the air.
  • barometric pressure refers hereinafter to the pressure within the atmosphere of Earth.
  • high throughput refers hereinafter to the use of equipment, automation equipment or partial thereof to permit rapid, highly parallel research or to provide results of the tests being conducted. It could address biological questions that are otherwise unattainable using conventional methods. It may incorporate techniques from optics, physics, chemistry, biology or image analysis.
  • Metal refers herein to any material engineered to have a property that is not found in naturally occurring materials. They are made from assemblies of multiple elements fashioned from composite materials such as metals and plastics. The materials are usually arranged in repeating patterns, at scales that are smaller than the wavelengths of the phenomena they influence. Metamaterials derive their properties not from the properties of the base materials, but from their newly designed structures. Their precise shape, geometry, size, orientation and arrangement gives them their smart properties capable of manipulating electromagnetic waves: by blocking, absorbing, enhancing, or bending waves, to achieve benefits that go beyond what is possible with conventional materials.
  • metamaterials can affect waves of electromagnetic radiation or sound in a manner not observed in bulk materials. Those that exhibit a negative index of refraction for particular wavelengths have attracted significant research. These materials are known as negative-index metamaterials.
  • PET Polyethylene terephthalate, PET refers herein to the most common thermoplastic polymer resin of the polyester family and is used in fibers for clothing, containers for liquids and foods, thermoforming for manufacturing, and in combination with glass fiber for engineering resins.
  • Linear discriminant analysis refers herein after to a normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics, pattern recognition, and machine learning to find a linear combination of features that characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.
  • the present invention utilizes Fisher's linear discriminant and/or Fisher's nonlinear discriminant.
  • k- nearest neighbors algorithm refers to a non-parametric method used for classification and regression.
  • the input consists of the k closest training examples in the feature space.
  • the output depends on whether k-NN is used for classification or regression:
  • the output is a class membership.
  • the output is the property value for the object. This value is the average of the values of k nearest neighbors.
  • &-NN is a type of instance-based learning, or lazy learning, where the function is only approximated locally and all computation is deferred until classification.
  • a useful technique can be to assign weights to the contributions of the neighbors, so that the nearer neighbors contribute more to the average than the more distant ones.
  • a common weighting scheme consists in giving each neighbor a weight of 1 Id, where d is the distance to the neighbor.
  • the neighbors are taken from a set of objects for which the class (for k-NN classification) or the object property value (for &-NN regression) is known. This can be thought of as the training set for the algorithm, though no explicit training step is required.
  • the present invention relates to the use of Terahertz (THz) in detection of healthy (Covid-19 free or recovered) individuals vs. Covid-19 infected individuals.
  • THz radiation generally refers herein below to any of the electromagnetic wave frequencies that he in the range extending from around 100 GHz to 30 THz.
  • THz has great advantages over IR and UV as the sensitivity and the detection threshold is very low thus, can detect information relating to Covid-19 (as will be described herein below), at very early stages thereof.
  • IR and UV can detect information relating to Covid-19 at very late stages of the disease.
  • the information that can be detected is selected from a group consisting of cell unit of said virus, viral proteins, cellular debris, debris of said virus, hydrates of said virus, hydrates of debris of said virus, hydrates of the 3D structure of said virus and a cell, aggregates of said virus, cytokines, increased level of interleukin (IL)-2, IL-7, granulocytecolony, stimulating factor, interferon-g, inducible protein 10, monocyte chemoattractant, protein 1, macrophage, inflammatory protein 1-a, and tumor necrosis factor-a and any combination thereof.
  • IL interleukin
  • the advantages of the present invention include, inter alia, the following: Early Detection of Asymptomatic carriers of COVID-19; Fast Coronavirus Test detection - up to 1 minute; preferably less than 40 sec; High Throughput - -800-1, 500/Tests/Day; and, Non- Invasive - the testing includes blowing several times into the sampler.
  • the present invention provides a label free, noncontact, non-invasive method for the detection of COVID-19, without the need to amplify the DNA sample, 1st, 2nd and 3rd virus waves of the infection.
  • the term ’’collected media refers hereinafter to any volatiles compound, VC, and/or aerosol and/or any chemical and biological compounds transmitted airborne that were released in the breath by at least one individual being tested.
  • volatiles or “volatiles compound” or “VCs” generally refers herein below to volatile compound and/or mix of compounds.
  • the VCs can be organic compound and/or mix of compounds or inorganic compound and/or mix of compounds. It is also within the scope of the present invention wherein the VC is a mix of organic and inorganic compound ⁇ s.
  • the present invention provides a label free, noncontact, non-invasive method for the detection of COVTD-19, without the need to amplify the DNA sample, 1st, 2nd and 3rd virus waves of the infection.
  • the present invention provides a breathalyzer or breathalyzer- like device that will enable the detection of COVTD-19 in the exhaled breath of humans.
  • COVID-19 is infectious by droplets and contact
  • testing the infectious agent in the breath and not from the blood stream is advantageous.
  • the severity of the disease can be diagnosed.
  • the present invention provides a membrane metamaterial absorber for different virus detection based on detection of trends of spoof surface plasmon polaritons (SSPPs) in THz band.
  • SSPPs surface plasmon polaritons
  • the exhaled breath of humans will contain VCs and/or aerosols that will be captured in the membrane (e.g., made of PET or open-cell foam-based melamine) and will create SSPPs. Detection of specific trends in the absorption spectrum in THz bands.
  • SPPs surface plasmon polaritons
  • EM electromagnetic
  • SPPs are not supported below the far-infrared frequency because the strong field confinement no longer exists. In fact, at lower frequencies, metals behave close to perfectly electric conductors (PECs) rather than plasmas at optical frequencies.
  • PECs perfectly electric conductors
  • the first “artificial” surface plasmon polaritons are termed as the spoof SPPs.
  • Spoof SPPs To produce spoof SPPs at Terahertz frequencies, plasmonic metamaterials are utilized to provide subwavelength structures on a metal surface. Spoof SPPs inherit the properties of natural SPPs, including dispersion characteristics, field confinement, and subwavelength resolution, and therefore are highly expected to offer new solutions for advanced circuits and systems with high integration, compact size, and excellent performance.
  • THz technology enables the detection of COVTD-19 infected or COVTD-19- free (healthy) individuals, by means of label-free, noncontact, noninvasive, and nondestructive method.
  • the technique of the present invention is capable of detecting a trends in the absorption spectrum of spoof surface plasmon polaritons (SSPPs) (captured in the membrane and created due to VCs and/or aerosols in the exhaled breath of health people) due to the THz spectroscopy technique being capable of detection of mater ials/compounds at very low concentrations, below PPB (parts per billion).
  • SSPPs spoof surface plasmon polaritons
  • Volatiles emitted from the breath convey information on the person being infected with COVTD-19 or a healthy one.
  • Said VCs and/or aerosols will be captured in the membrane (e.g., made of PET or open-cell foam-based melamine) can cause the creation of SSPPs.
  • the membrane will be irradiated with THz frequencies and the absorption spectrum thereof will be analyzed. The same is true for healthy individuals. By identifying different trends, the identification of COVTD-19 infected or COVTD-19 free (healthy) people could be identified.
  • a membrane metamaterial absorber for different virus detection in THz band will be integrated in a breathalyzer.
  • the identification of strongly confined SSPPs modes, extracted from the absorption spectra of biosensing metamaterial absorber, like trends signature, will provide identification and detection of the virus’ infected and virus- free (healthy) individuals; namely in COVTD-19.
  • the proposed THz biosensing metamaterial absorber chip will perform ultrasensitive, high resolution detection by extracting the shifted resonance frequencies (AF) and the changed values at maximum absorptions (DA). Each virus species will have a dedicated fingerprint signature in terms of the AF and DA.
  • the absorption will provide an indication as to the severity of the disease.
  • the collection system (the breathalyzer) will comprises the membrane biosensing chip and an integrated THz detection by means of a VCSEF (Vertical Cavity Surface Emitting Laser) that can be implemented in handheld devices.
  • VCSEF Very Cavity Surface Emitting Laser
  • the collection system (the breathalyzer) will be in communication with a THz detection system.
  • the membrane can be a pressure permeable membrane (e.g., Meta-Material Membrane (MMM) or Semi Pressure Permeable Membrane, e.g., meta-material PET or open-cell foam- based melamine based membrane).
  • MMM Meta-Material Membrane
  • Semi Pressure Permeable Membrane e.g., meta-material PET or open-cell foam- based melamine based membrane
  • Vacuum can also be applied to accelerate the flow of the air (from the exhaled air). Then, after the exhaled air has been sampled, the membrane are scanned with THz waves and the specific is detected based.
  • a system for detecting COVID-19 infected or free (healthy) people by means of the detection of trends in the absorption spectra of said metamaterial absorber membrane by scanning thereof with electromagnetic radiation in the THz range.
  • the membrane (with the collected SSPPs from the breath trapped therewithin) is scanned with an electromagnetic radiation in the THz range, and processing the data for identifying a signature being indicative of at least one COVID-19 property to thereby generate information data being indicative of at least one COVID-19 infected or free (healthy) individuals.
  • membrane metamaterial absorber or “biosensing metamaterial absorber chip” refer to a membrane being capable of trapping collected SSPPs and VCs and/or aerosols from a human breath therein.
  • the membrane is integrated in a breathalyzer.
  • the membrane is made of PET or open-cell foam-based melamine and any combination thereof.
  • the membrane is placed in a PTFE (Polytetrafluoroethylene, aka. Teflon) disposable holder.
  • PTFE Polytetrafluoroethylene
  • the capsule is a disposable, sterile PTFE (Polytetrafluoroethylene, aka. Teflon) - based capsule.
  • sampler or “disposable, hand-held tube” refers hereinafter to the sampler with which the breath sample from the tested individual is taken.
  • sampler is made of polyoxymethylene-based (aka Delrin).
  • LOO Leave One Out
  • the training is performed repeatedly, each time after excluding one training sample from the training data of the group, and then testing on those individual vectors that were excluded from training. Based on that specific learning process of LOO, a prediction is made for the left-out spectra and compared to the actual PCR results.
  • the term "Principal Component Analysis” refers hereinafter to mathematical technique. According to said technique, the mean (symbol below as “m”) is subtracted from each spectrum (after being normalized by its associated reference) and the covariance (symbol below as small sigma as standard deviation) matrix of the combined spectra is computed. The eigen-values of this matrix are found, and the largest values are used to compute their respective eigen-vectors. This procedure is essentially a linear transformation of the normalized spectra into a set of vectors that best represent the training samples and are less prone to noise. These eigen-vectors (also called feature vectors) are then used to obtain a set of co-efficient vectors, one for each input spectrum, whose length equals the number of the feature vectors selected.
  • the tested individuals are sampled in the breathalyzer (it could be aided by the use of vacuum suction), and the VCs and/or aerosols are trapped in a pressure dischargeable membrane (e.g., Meta-Material Membrane (MMM) Semi Pressure Permeable Membrane, e.g., meta-material PET or open- cell foam-based melamine based membrane), such that when the breath is exhaled by the human, the membrane is located at the propagation path of the VCs and/or aerosols released from the human.
  • MMM Meta-Material Membrane
  • MMM Meta-Material Membrane
  • Semi Pressure Permeable Membrane e.g., meta-material PET or open- cell foam-based melamine based membrane
  • the membrane is scanned with THz waves and the specific VCs and/or aerosols for infected or healthy tested are detected based on the individual fingerprints trends in the adsorption.
  • the membrane is then capable of rel easing/ discharging the trapped vapors by an operation including also positive or negative pressure.
  • the system may also comprise a control unit configured and operable for receiving data indicative of the collected VCs and/or aerosols being scanned with an electromagnetic radiation in the THz range, and processing the data for identifying a signature being indicative of an infected COVTD-19 individual and a healthy one.
  • a control unit configured and operable for receiving data indicative of the collected VCs and/or aerosols being scanned with an electromagnetic radiation in the THz range, and processing the data for identifying a signature being indicative of an infected COVTD-19 individual and a healthy one.
  • a control unit is configured to receive and process the response signal emitted by the membrane and identify spectral special features indicative of a THz signature of the COVTD-19 infected or free (healthy) individual.
  • the inventors found that COVID-19 has its own THz signature. Thus, individual human can be distinguished from healthy ones.
  • the control unit is configured and operable for performing a pattern recognition of the THz signature.
  • the control unit is configured generally as a computing/electronic utility including inter alia such utilities as data input and output utilities, memory, and data processing utility.
  • the utilities of the control unit may thus be implemented by suitable circuitry and/or by software and/or hardware components including computer readable code configured for implementing the operations method.
  • the features of the present invention may comprise a general-purpose or special- purpose computer system including various computer hardware components, which are discussed in greater detail below.
  • Features within the scope of the present invention also include computer-readable media for carrying or having computer-executable instructions, computer-readable instructions, or data structures stored thereon.
  • Such computer-readable media may be any available media, which are accessible by a general-purpose or special- purpose computer system.
  • Such computer-readable media can comprise physical storage media such as RAM, ROM, EPROM, flash disk, CD- ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other media which can be used to carry or store desired program code means in the form of computer-executable instructions, computer-readable instructions, or data structures and which may be accessed by a general-purpose or special-purpose computer system.
  • Computer-readable media may include a computer program or computer application downloadable to the computer system over a network, such as a wide area network (WAN), e.g. Internet.
  • WAN wide area network
  • a "control unit” is defined as one or more software modules, one or more hardware modules, or combinations thereof, which work together to perform operations on electronic data.
  • processing utility includes the hardware components of a personal computer, as well as software modules, such as the operating system of a personal computer. The physical layout of the modules is not relevant.
  • a computer system may include one or more computers coupled via a computer network.
  • a computer system may include a single physical device where internal modules (such as a memory and processor) work together to perform operations on electronic data. While any computer system may be mobile, the term “mobile computer system” or the term “mobile computer device” as used herein especially includes laptop computers, netbook computers, cellular telephones, smartphones, wireless telephones, personal digital assistants, portable computers with touch sensitive screens, and the like.
  • the control unit of the present invention may be implemented as part of a signal processing center, and/or as a portable (e.g. handheld) THz reading device.
  • Data input utility includes a communication module for receiving the response THz signal, an optional data output utility for generating data relating to identified virus(s), a memory (i.e. non- volatile computer readable medium) for storing a learning database i.e. preselected data indicative of THz signatures of the Spoof SPPs and therefore of the virus, and a data processing utility adapted for identifying the COVTD-19 infected or free (healthy) individuals.
  • the database may be implemented with Microsoft Access, Cybase, Oracle, or other suitable commercial database systems.
  • the system is configured in a cloud-based configuration and/or utilize Internet based computing so that parts of processing utility, and/or memory may reside in multiple distinct geographic locations.
  • the data processing utility is enabled to process the signal(s). Results of the signal processing step may be displayed and/or stored in storage and/or sent to a data communication unit for transfer to a sorting device.
  • the memory may include instructions executable by data processing utility. The instructions may be operable to enable data processing utility to receive the THz response signal(s), to process the THz response signal (s), to identify at least one fingerprint signature of the absorption spectrum of a membrane to which VC (from the exhaled breath of human) will be captured therewithin (to create Spoof SPPs).
  • the membrane will be irradiated with THz frequencies.
  • the absorption spectrum will be analyzed to find trends indicative of the virus, and to output via the data output utility a notification regarding the detection or failure to detect the virus (i.e., the infected with COVTD-19 individuals).
  • Memory and may be relayed via wireless or wired connection by an external unit to a central database.
  • the control unit activates a spectroscopy assembly configured and operable for obtaining the THz signature.
  • Spectroscopic assembly may or may not be a part of the system of the present invention.
  • the system is a breathalyzer and the spectroscopy assembly (in the THz range) is integrated within the system.
  • the THz capabilities are based on a VCSEL (Vertical Cavity Surface Emitting Laser) and can be integrated in IOT devices as well as handheld devices.
  • the spectroscopy assembly in not integrated in the system and the absorption spectrum is communicated to said spectroscopy assembly to be analyzed.
  • the processing utility signals to THz radiation transmitter unit to emit THz radiation passing though the membrane (being in the optical path of the THz radiation).
  • Data input receives a radiation signal pattern via radiation detection unit.
  • the radiation signal pattern is the radiation that was not adsorbed by the membrane.
  • the radiation signal pattern contains the THz signature.
  • Processing utility may transmit data regarding the signal pattern via the data output utility, via a data communication (e.g. via cellular network) to a communication module of a central computer.
  • the processing utility may record the received data in a learning database in memory and/or may query/cross- reference the received data with data in the learning database to identify virus properties and may communicate such data to a mobile device at which processing utility may signal to display a message corresponding to the virus data.
  • the preselected data stored in the learning database may be used to compare the THz pattern/ signature of the VCs and/or aerosols (captured in the membrane and created the Spoof SPPs) with the signatures or trends stored in the learning database.
  • the membrane metamaterial absorber may be a pressure permeable membrane configured as a dense, compressed structure made of fibers (e.g. mesh) such that the pressure permeable membrane responds to the application/release of vacuum as a pressure dischargeable membrane.
  • the membrane metamaterial absorber may be configured as a metamaterial membrane being a material deriving its properties not from the properties of the basic materials, but from its designed structure.
  • the metamaterial membrane may comprise a plurality of layers of metamaterial encapsulated in a plastic housing, produced with an accuracy of ⁇ 10 microns.
  • the system includes a spectroscopic assembly including a radiation transmitter unit being configured and operable to produce THz frequency radiation and a detection unit being configured and operable to detect an electromagnetic radiation emitted/influenced by the spoof surface plasmon polaritons (SSPPs) and/or the VCs and/or aerosols captured in the membrane.
  • the radiation transmitter unit is operable for irradiating the membrane with a radiation having a wavelength in the range extending from around 100 GHz to 30 THz and to scan the membrane within a scanning window of about 100 GHz.
  • the radiation transmitter unit and the detection unit are represented as two separate physical elements, they can be integrated in the same physical element or in the same housing.
  • radiation transmitter unit is configured and operable for generating inspecting and reference electro-magnetic radiation components of substantially the same frequency contents, and for sweeping/scanning the frequency.
  • Detection unit may be located in a first path of the inspecting radiation components after passing through the membrane and in a second path of the reference radiation component directly propagating from the transmitter unit.
  • the spectroscopic assembly may be configured to induce a predetermined frequency difference between a frequency of the inspecting radiation component and the reference radiation component interacting at the detection unit such that a signal resulting from the interaction between the inspecting and reference components is indicative of one or more properties of the virus at a location where the inspecting radiation interacts with the membrane.
  • the system (breathalyzer) of the present invention may comprise the spectroscopy assembly as described above or may directly receive data emitted by the VCs and/or aerosols (and/or the spoof surface plasmon polaritons (SSPPs)) in the membrane obtained by an external spectroscopy assembly as described above or as conventionally used in the field.
  • the spectroscopy systems include photo-mixing, heterodyne detection, and chirped- pulse THz spectroscopy. Another spectroscopy method is to use the THz resonance field in a photonic crystal, a waveguide device or frequency multiplier.
  • the system is connectable to a communication network with a host computer, which is external to the control unit.
  • the spectroscopic assembly can be also attached to the control unit by using a coupling member of any type.
  • the control unit is configured and operable to control the operation of the spectroscopic assembly.
  • the control unit may be integrated within the spectroscopic assembly or may be a separate element communicating with the spectroscopic assembly via wired or wireless communication. If the control unit is integrated within the spectroscopic assembly, THz signature identification does not require or employ any type of electronic components, circuitry or antenna. It should be appreciated, that signal exchange and communication is enabled between the modules of the system by virtue of appropriate wiring, or wirelessly.
  • the spectroscopic assembly and the control unit can be connected by IR (Infra-Red), RF (radio frequency including Bluetooth) or cable control. If the spectroscopic assembly and the control unit are integrated in the same physical housing, the THz signature is stored in the control unit.
  • the connections as discussed herein may be any type of connection suitable to transfer signals from or to the respective nodes, units or devices, for example via intermediate devices. Accordingly, unless implied or stated otherwise, the connections may for example be direct connections or indirect connections.
  • the connections may be illustrated or described in reference to being a single connection, a plurality of connections, unidirectional connections, or bidirectional connections. However, different embodiments may vary the implementation of the connections.
  • unidirectional connections may be used rather than bidirectional connections, and vice versa.
  • a plurality of connections may be replaced with a single connection that transfers multiple signals serially or in a time multiplexed manner.
  • single connections carrying multiple signals may be separated out into various different connections carrying subsets of these signals. Therefore, many options exist for transferring signals.
  • the thickness of the membrane may be selected to be at least several times (e.g. at least four times) the wavelength of the electromagnetic radiation.
  • the thickness should be selected to be sufficiently wide to enable to capture a sufficient amount of spoof surface plasmon polaritons (SSPPs) allowing to perform an analysis providing an identifiable THz signature.
  • SSPPs spoof surface plasmon polaritons
  • the THz signature is sensitive to low changes in the vapor composition and provides a detection with high resolution.
  • the high resolution of the THz signature enables to differentiate between signatures of different viruses. If the resolution of the signature is not good enough, the THz signatures would overlap and a differentiation between them is then impossible.
  • the use of infrared radiation does not provide an identifiable signal.
  • a spectroscopic analysis using an infrared radiation including the collection of the gas and the separation of the different chemical components, yields poor results.
  • the high rate of gas delivery required by the infrared spectroscopy does not permit collection of the carrier and separated components in a small area.
  • the detection method may comprise the step of obtaining a reference spectrum by performing a THz spectroscopy on a reference clean membrane. In some embodiments, the method may comprise the step of cleaning a membrane having trapped VCs and/or aerosols for a further use by applying a positive/negative pressure.
  • the method may further comprises a step of recording a THz signature in the learning database.
  • the learning database may be configured to provide a THz fingerprint/signature associated with the one or more absorption spectrum of VCs and/or aerosols from COVTD-19 infected or free (healthy) individuals.
  • the method may include storing in the learning database preselected data indicative of the signature of the signal and/or properties of the VCs and/or aerosols associated with COVTD-19 infected or free (healthy) individuals with the signature.
  • the step of processing the data may further include comparing the received THz data to data in the learning database. Received THz data may be logged in a learning database. Logged received THz data may be used for future analyses of future viruses.
  • step of processing the data may further include assessing one or more properties of the trends in absorption spectrum of VCs and/or aerosols or spoof surface plasmon polaritons (SSPPs) as indicative to the COVTD-19 infected or free (healthy) individuals, based on the learning database data. Assessing one or more properties may be performed using a statistical analysis in which received THz data is compared to learning database THz data and a statistical comparison is performed. If a predetermined level of similarity is shown, the THz data is considered to have a certain property.
  • SSPPs surface plasmon polaritons
  • the processing of the control unit comprises the step of providing a mathematical interpretation of pattern recognition based on a learning algorithm such as a Neural Network Acceleration algorithm (NNA).
  • NNA Neural Network Acceleration algorithm
  • the interpretation of the pattern recognition is based on identification of special features of the pattern such as the identification of main and side peaks, the number of main and side peaks, the width of the peaks and the distance between them.
  • the membrane with be coated with Silicon or Silicon Graphene, acting as a reflector, to enhance the signal.
  • the processing step may comprise the following steps: an optional preprocessing step being configured to remove irrelevant spectral trends present in the measurements, and to filter out random measurement noise; a feature extraction step being configured to estimate the most relevant vectors defining the data using a principal component analysis; and a pattern classification step using a combined linear and nonlinear pattern recognition approach.
  • the optional preprocessing step may include the step of establishing the learning database.
  • the step of establishing the learning database may comprise the steps of collecting the scans, preprocessing the scans as described above, and performing a Fourier Transformation on the results.
  • the feature extraction step may include the step of subtracting a reference processed data from the sample processed data.
  • the resulting data belongs to or represents only VCs’ and/or aerosols’ virus related information (without data relating to the membrane).
  • the step of subtracting the reference processed data (e.g. membrane results) from the sample processed data (e.g. virus sample results) may be followed by a step of performing a second Fourier transformation on the virus related information to provide the specific virus related signals.
  • the pattern classification step may include the steps comparing all the obtained results to the learning database.
  • the learning database is established, the same sampled membrane are tested biologically by Polymerase Chain Reaction (PCR) method for the COVID-19 detection.
  • PCR Polymerase Chain Reaction
  • the absorption spectra is read and compared to a database via software matching algorithms.
  • the database contains spectral fingerprints of the trends in the absorption spectra (obtained from scanning the membrane with the VCs and/or aerosols captured therewithin) with a specified signature or trend/s therewithin representing detection of COVID-19 infected or free (healthy) individual.
  • terahertz radiation within the 200-1200 GHz range is used.
  • the software matching algorithm compares the collected spectrum to the catalogued fingerprint within pre- determined confidence bounds, and detects the virus by determining whether or not the read spectrum falls within the error bounds of the fingerprint.
  • membranes may be recycled via application of electricity to release the VCs and/or aerosols and/or spoof surface plasmon polaritons (SSPPs) from the membrane.
  • the "cleaned" membrane is cycled back into place on the sampling apparatus.
  • the membrane can be cleaned by reversing the flow of the vacuum motor, which causes air to pass through the membrane and push the absorbed molecules from the membrane.
  • each membrane may be used only once and then replaced by a new membrane.
  • the mathematical analysis is described below. After establishing the learning data base, all next measured data is compared to the learning database by using the same mathematical process.
  • the inventors of the present invention have found that different THz signatures being indicative of different properties of viruses can be detected.
  • the present invention can detect VCs and/or aerosols from infected or free (healthy) COVTD- 19 individual.
  • the inventors of the present invention believe that the identification of the special features of the pattern such as the number of peaks, the distance between the main peaks, the identification of main and side peaks, the width of the peaks enables to define the properties of the virus.
  • the inventors have found that obtaining a ratio between the THz signatures of different membrane enables identification of infected and healthy individuals.
  • NNA Neural Network Analysis
  • Leave One Out (LOO) algorithm is the one of the methods that could be used for the analysis of the Terahertz spectra detection, in order to provide accurate detection of the virus.
  • LOO is a statistical method used to evaluate the efficacy of any classification procedure, with a relatively low number of samples, in order to teach and train spectroscopy systems to analyze spectral vectors.
  • the training is performed repeatedly, each time after excluding one training sample from the training data of the group, and then testing on those individual vectors that were excluded from training. Based on that specific learning process of LOO, a prediction is made for the left-out spectra and compared to the actual PCR results.
  • each spectral vector is made by either using a linear classification method (see Fisher R.A. The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics, 7 Part II: 179-188, 1936) or using the Mahalanobis distance classifier (see Mahalanobis, P.C. On the generalized distance in statistics. Proceeding of the National Institute of Sciences of India. 2(1):49:55). Both methods use the classes' means and covariances to assign each input vector to its own class based on its multi- dimensional distances from each class. Therefore, the results obtained clearly indicate that this procedure is adequate for classifying unseen spectra into their associated classes, with a high probability of detection and low “false-alarm” rates.
  • the method is based on a "Principal Component Analysis” (see Konstantinos, I.D. and Sun-Yuang, K. Principal Component Neural Networks: Theory and Applications. Wiley-Inter-science, New York, 1996).
  • the mean symbol below as “m”
  • the covariance symbol below as small sigma as standard deviation
  • This procedure is essentially a linear transformation of the normalized spectra into a set of vectors that best represent the training samples and are less prone to noise.
  • eigen-vectors also called feature vectors
  • These eigen-vectors are then used to obtain a set of co-efficient vectors, one for each input spectrum, whose length equals the number of the feature vectors selected.
  • the purpose of the spectral classification stage is to train the algorithm, by using a known set of spectra and then to classify previously unseen spectra into their respective classes, with a minimal number of errors.
  • the target for 100% separation is J>19 (as shown in the equation above).
  • the membrane is made of hardened extruded plastic, containing pores of two specific sizes, and acting as Ketones trap.
  • the compound could also be , 1 -butanol, dimethyl disulfide, methyl benzene, hexanal, phenylethane, heptanal, benzaldehyde, dimethyl trisulfide, phenol, 2-(2- ethoxyethoxy)ethanol, 2-ethyl- 1 -hexanol, 5 -isopropeny 1- 1 -methyl- 1 cyclohexene, acetophenone, 2-nonanone, 2-decanone, 2-isopropylphenol, benzothiazole, 2-undecanone, 1,3-diacetylbenzene, diethyl phthalate, 1,3-diphenyl propane, Ammonia, Greenhouse gases selected from Water vapor Methane (CH4), Carbon dioxide (C02),
  • According to another embodiment of the present invention is to provide a single- use, disposable membranes. According to another embodiment the membrane is reusable.
  • LDA k-nearest neighbors algorithm
  • k-NN k-nearest neighbors algorithm
  • THz radiation Terahertz (THz) radiation is known to interact with polar molecules via rotational or/and vibrational transition levels. These interactions are manifested as absorption.
  • the frequency THz spectrum obtained by scanning the membrane is indicative of various chemical materials including volatile compounds, VCs, and/or aerosols having individual specific fingerprints or trends.
  • control unit is configured to receive and process the response signal emitted by the testes individual and identify spectral special features indicative of a THz signature of the VCs and/or aerosols indicative of COVTD-19 infected or free (healthy) individual.
  • the information included in the THz signature is thus associated with the sorting process.
  • the system (breathalyzer) is configured to be used with at least one tested individual with exhaled breath having VCs and/or aerosols with properties identifiable by THz inspection, such that upon examination by THz analysis, infected individuals or individuals who are COVID-19 free (healthy) may be identified.
  • control unit is configured and operable for performing a pattern recognition of the THz signature.
  • the control unit is configured generally as a computing/electronic utility including inter alia such utilities as data input and output utilities, memory, and data processing utility.
  • the utilities of the control unit may thus be implemented by suitable circuitry and/or by software and/or hardware components including computer readable code configured for implementing the operations of methods described below.
  • the features of the present invention may comprise a general-purpose or special- purpose computer system including various computer hardware components, which are discussed in greater detail below.
  • Features within the scope of the present invention also include computer-readable media for carrying or having computer-executable instructions, computer-readable instructions, or data structures stored thereon.
  • Such computer-readable media may be any available media, which are accessible by a general-purpose or special- purpose computer system.
  • Such computer-readable media can comprise physical storage media such as RAM, ROM, EPROM, flash disk, CD- ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other media which can be used to carry or store desired program code means in the form of computer-executable instructions, computer-readable instructions, or data structures and which may be accessed by a general-purpose or special-purpose computer system.
  • Computer-readable media may include a computer program or computer application downloadable to the computer system over a network, such as a wide area network (WAN), e.g. Internet.
  • WAN wide area network
  • a "control unit” is defined as one or more software modules, one or more hardware modules, or combinations thereof, which work together to perform operations on electronic data.
  • processing utility includes the hardware components of a personal computer, as well as software modules, such as the operating system of a personal computer. The physical layout of the modules is not relevant.
  • a computer system may include one or more computers coupled via a computer network.
  • a computer system may include a single physical device where internal modules (such as a memory and processor) work together to perform operations on electronic data. While any computer system may be mobile, the term “mobile computer system” or the term “mobile computer device” as used herein especially includes laptop computers, netbook computers, cellular telephones, smartphones, wireless telephones, personal digital assistants, portable computers with touch sensitive screens, and the like.
  • the control unit of the present invention may be implemented as part of a signal processing center, and/or as a portable (e.g. handheld) THz reading device.
  • Data input utility includes a communication module for receiving the response THz signal, an optional data output utility for generating data relating to identified healthy individuals, infected ones, a memory (i.e. non-volatile computer readable medium) for storing a learning database i.e. preselected data indicative of THz signatures of the healthy individuals versus the infected ones, and a data processing utility adapted for identifying infected or healthy ones.
  • the database may be implemented with Microsoft Access, Cybase, Oracle, or other suitable commercial database systems.
  • the system is configured in a cloud-based configuration and/or utilize Internet based computing so that parts of processing utility, and/or memory may reside in multiple distinct geographic locations.
  • the data processing utility is enabled to process the signal(s).
  • Results of the signal processing step may be displayed and/or stored in storage and/or sent to a data communication unit for transfer to a sorting device.
  • the memory may include instructions executable by data processing utility. The instructions may be operable to enable data processing utility to receive the THz response signal(s), to process the THz response signal (s), to identify at least one property in the absorption spectrum of the membrane (captured with the VCs and/or aerosols), and to output via the data output utility a notification regarding if the individual is healthy or infected.
  • control unit activates a spectroscopy assembly configured and operable for obtaining the THz signature.
  • Spectroscopic assembly may or may not be a part of the system of the present invention.
  • the processing utility signals to THz radiation transmitter unit to emit THz radiation passing though the membrane (being in the optical path of the THZ radiation).
  • Data input receives a radiation signal pattern via radiation detection unit.
  • the radiation signal pattern is the radiation that was not adsorbed by the membrane.
  • the radiation signal pattern contains the THz signature.
  • Processing utility may transmit data regarding the signal pattern (such as infected or healthy) via the data output utility, via a data communication (e.g. via cellular network) to a communication module of a central computer.
  • the processing utility may record the received data in a learning database in memory and/or may query/cross-reference the received data with data in the learning database to identify the properties and may communicate such data to a mobile device at which processing utility may signal to display a message corresponding to the data.
  • the preselected data stored in the learning database may be used to compare the THz pattern/ signature of the collected volatile compounds (organic or inorganic) and/or aerosols with the signatures of healthy or infected COVTD-19 individuals stored in the learning database.
  • Vacuum may also be applied to ease suction of the VCs and/or aerosols (once a human exhale breath into the system, i.e., into the breathalyzer).
  • the working range of vacuums which may be employed is about 600 mmHg for a short time period.
  • the time range for application of these vacuums is from about one second to five seconds.
  • Identification of infected or healthy individual would be enabled by time period of less than 60 seconds. More specifically less than 30 seconds; even more specifically less than 20 seconds.
  • the membrane may be a pressure permeable membrane configured as a dense, compressed structure made of fibers (e.g. mesh) such that the pressure permeable membrane responds to the application/release of vacuum as a pressure dischargeable membrane.
  • the pressure dischargeable membrane may be configured as a metamaterial membrane being a material deriving its properties not from the properties of the basic materials, but from its designed structure.
  • the metamaterial membrane may comprise a plurality of layers of metamaterial encapsulated in a plastic housing, produced with an accuracy of ⁇ 10 microns.
  • the system includes a spectroscopic assembly including a radiation transmitter unit being configured and operable to produce THz frequency radiation and a detection unit being configured and operable to detect an electromagnetic radiation emitted by the collected volatile compounds and/or aerosols.
  • radiation transmitter unit is operable for irradiating the membrane with a radiation having a wavelength in the range extending from around 100 GHz to 30 THz and to scan the permeable membrane holding the collected volatile compounds and/or aerosols within a scanning window of about 100 GHz.
  • the radiation transmitter unit and the detection unit are represented as two separate physical elements, they can be integrated in the same physical element or in the same housing.
  • radiation transmitter unit is configured and operable for generating inspecting and reference electro-magnetic radiation components of substantially the same frequency contents, and for sweeping/scanning the frequency.
  • Detection unit may be located in a first path of the inspecting radiation components after passing through the membrane and in a second path of the reference radiation component directly propagating from the transmitter unit.
  • the spectroscopic assembly may be configured to induce a predetermined frequency difference between a frequency of the inspecting radiation component and the reference radiation component interacting at the detection unit such that a signal resulting from the interaction between the inspecting and reference components is indicative of one or more properties of the VCs and/or aerosols indicative of COVID-19 infected individuals at a location where the inspecting radiation interacts with the membrane (capturing the VCs and/or aerosols).
  • the system (breathalyzer) of the present invention may comprise the spectroscopy assembly as described above or may directly receive data emitted by the collected volatile compounds and/or aerosols obtained by an external spectroscopy assembly as described above or as conventionally used in the field.
  • one spectroscopy method is to radiate THz waves directly on the membrane itself and acquire their spectral information, such as the fingerprint feature or decay signals of a pulse as response signals.
  • the spectroscopy systems include photo-mixing, heterodyne detection, and chirped-pulse THz spectroscopy.
  • Another spectroscopy method is to use the THz resonance field in a photonic crystal, a waveguide device or frequency multiplier.
  • the membrane is located at the propagation path of the volatile compounds and/or aerosols.
  • the membrane is also positioned within the optical path of the electromagnetic radiation emitted by the transmitter unit.
  • the membrane may be spaced-apart from spectroscopic assembly.
  • the membrane is interrogated by the spectroscopic assembly.
  • the membrane may be a part of the spectroscopic assembly.
  • the system is connectable to a communication network with a host computer, which is external to the control unit.
  • the spectroscopic assembly can be also attached to the control unit by using a coupling member of any type.
  • the control unit is configured and operable to control the operation of the spectroscopic assembly.
  • the control unit may be integrated within the spectroscopic assembly or may be a separate element communicating with the spectroscopic assembly via wired or wireless communication.
  • THz signature identification does not require or employ any type of electronic components, circuitry or antenna. It is not shown in detail, but should be appreciated, that signal exchange and communication is enabled between the modules of the system by virtue of appropriate wiring, or wirelessly.
  • the spectroscopic assembly and the control unit can be connected by IR (Infra-Red), RF (radio frequency including Bluetooth) or cable control. If the spectroscopic assembly and the control unit are integrated in the same physical housing, the THz signature is stored in the control unit.
  • the connections as discussed herein may be any type of connection suitable to transfer signals from or to the respective nodes, units or devices, for example via intermediate devices.
  • connections may for example be direct connections or indirect connections.
  • the connections may be illustrated or described in reference to being a single connection, a plurality of connections, unidirectional connections, or bidirectional connections. However, different embodiments may vary the implementation of the connections. For example, separate unidirectional connections may be used rather than bidirectional connections, and vice versa.
  • a plurality of connections may be replaced with a single connection that transfers multiple signals serially or in a time multiplexed manner.
  • single connections carrying multiple signals may be separated out into various different connections carrying subsets of these signals. Therefore, many options exist for transferring signals.
  • the transmitter unit is placed at a certain distance from the membrane.
  • the distance between the transmitter unit and the membrane may be selected to be at a close proximity being less than the wavelength of the electromagnetic radiation. For example, this distance may be selected to be below 1 mm for a radiation in the range of about 200 GHz to 1200 GHz. In a specific and non- limiting example, the distance between the transmitter unit and the membrane is selected to be in the range of about 0.599 - 0.749 mm. In this connection, it should be understood that, due to the propagation path in the THz range, if the distance between the transmitter unit and the membrane is selected to be less than the wavelength of the electromagnetic radiation, the result signal(s) will be screened from the environment (i.e.
  • the short distance between the transmitter unit and membrane eliminates the absorbance of the THz signal by the environment.
  • the thickness of the membrane may be selected to be at least several times (e.g. at least four times) the wavelength of the electromagnetic radiation.
  • the thickness should be selected to be sufficiently wide to enable to capture a sufficient amount of volatile compounds and/or aerosols allowing to perform an analysis providing an identifiable THz signature.
  • the membrane is configured and operable for trapping the collected volatile compounds and/or aerosols within a period of time being less than 60 sec. more preferable, less than 30 sec.
  • the capability of the system to identify a THz signature provides a fast inspection rate, being a significant parameter for quickly identifying COVTD-19 infected or free (healthy) individuals.
  • the THz radiation is capable of providing an identifiable signature even when the collected volatile compounds and/or aerosols are present in the vapor collection in a very-low concentration below PPB.
  • the THz signature is sensitive to low changes in the vapor composition and provides a detection with high resolution. The high resolution of the THz signature enables to differentiate between signatures of different viruses or from a healthy individual to a COVTD-19 infected individual.
  • the use of infrared radiation does not provide an identifiable signal.
  • the high rate of gas delivery required by the infrared spectroscopy does not permit collection of the carrier and separated components in a small area.
  • the period of time for collecting a certain amount of volatile compounds and/or aerosols which can be spectroscopically analyzed by using infrared radiation is much higher. For example, the time consumed to be able to obtain an identifiable infrared spectral data is about half an hour.
  • the concentration of the volatile compounds and/or aerosols in the aforementioned approach is too low to yield adequate infrared absorption. In other words, much higher concentrations are needed to provide an identifiable signal.
  • the use of Raman techniques can provide an identifiable signal even with low concentrations of the volatile compounds and/or aerosols, however, the data collection time is much longer than with the technique of the present invention and is therefore not suitable for commercial use.
  • techniques known in the art using THz spectroscopy provide a spectral analysis of each chemical component of the collected volatile compounds and/or aerosols, separately indicating the presence of concentration of each collected volatile compound, which is highly time consuming. Since the period of time spent for trapping a minimal quantity of collected volatile compounds and/or aerosols being in a sufficient concentration for providing an identifiable signature is less than 20 sec.
  • the following description provides a flow chart exemplifies the system operation for identifying COVTD-19 infected or COVTD-19 free (healthy) individuals.
  • the method comprises the steps of receiving data indicative of collected volatile compounds and/or aerosols being scanned with electromagnetic radiation in the THz range in step and processing the data for identifying a signature being indicative infected individuals/healthy individuals.
  • the step of processing may comprise step of performing a pattern recognition of the signature.
  • the method prior to receiving data indicative of collected volatile compounds and/or aerosols, the method further comprises performing a THz spectroscopy of the membrane.
  • This may be implemented by scanning the collected volatile compounds and/or aerosols captured in the membrane with an electromagnetic radiation in the THz range within a scanning window of about 100 GHz (e.g. by collecting 500 measurements).
  • This narrow scanning window enables to perform a fast scanning of the membrane and to reduce the period of time required for performing the inspection process.
  • this narrow scanning window also enables fast noise cancellation and an increase in accuracy of the measurements.
  • the method may comprise the step of trapping collected volatile and/or aerosols compounds by suction, wherein the trapping is performed within a period of time being less than 30 sec.
  • the method may comprise the step of obtaining a reference spectrum by performing a THz spectroscopy on a reference clean membrane being the same membrane used in the above. In some embodiments, the method may comprise the step of cleaning a membrane having trapped volatile compounds and/or aerosols for a further use by applying a positive/negative pressure.
  • performing a THz spectroscopy is implemented by scanning the membrane and collecting 500 measurements.
  • the spectral data is processed, the spectrum of the membrane obtained filled with VCs and/or aerosols (from exhaled breath) is compared to the reference spectral data.
  • method may further comprise the step of recording a THz signature in the learning database.
  • the learning database may be configured to provide a THz fingerprint/signature associated with the one or more VC found in exhaled breath in COVTD-19 free (healthy) individuals.
  • method may further comprise the step of recording a THz signature in the learning database.
  • the learning database may be configured to provide a THz fingerprint/signature associated with the one or more VC and/or aerosols found in exhaled breath in COVID-19 infected individuals.
  • the step of processing the data may further include comparing the received THz data to data in the learning database.
  • Received THz data may be logged in a learning database. Logged received THz data may be used for future analyses.
  • the step of processing the data may further include assessing one or more properties of an VCs and/or aerosols captured in the membrane based on the learning database data. Assessing one or more properties may be performed using a statistical analysis in which received THz data is compared to learning database THz data and a statistical comparison is performed. If a predetermined level of similarity is shown, the THz data is considered to have a certain property.
  • the membrane may be discharged of VCs and/or aerosols content via various methods which include desorption of VCs and/or aerosols and discharge with vacuum or high pressure flow.
  • the processing of the control unit comprises the step of providing a mathematical interpretation of pattern recognition based on a learning algorithm such as a Neural Network Acceleration algorithm (NNA).
  • NNA Neural Network Acceleration algorithm
  • the interpretation of the pattern recognition is based on identification of special features of the pattern such as the identification of main and side peaks, the number of main and side peaks, the width of the peaks and the distance between them.
  • the processing step of the method may comprise the following steps: an optional preprocessing step being configured to remove irrelevant spectral trends present in the measurements, and to filter out random measurement noise; a feature extraction step being configured to estimate the most relevant vectors defining the data using a principal component analysis; and a pattern classification step using a combined linear and nonlinear pattern recognition approach.
  • the optional preprocessing step may include the step of establishing the learning database.
  • the step of establishing the learning database may comprise the steps of collecting the scans, preprocessing the scans as described above, and performing a Fourier Transformation on the results.
  • a feature extraction step may include the step of subtracting a reference processed data from the sample processed data.
  • the resulting data belongs to or represents only membraned with VCs and/or aerosols captured therewithin related information (without data relating to the membrane).
  • the step of subtracting the reference processed data e.g. membrane results
  • the sample processed data e.g.
  • membraned with VCs and/or aerosols captured therewithin may be followed by a step of performing a second Fourier transformation on the membrane related information to provide the specific VCs and/or aerosols related signals, among them the infected/healthy partitioning signals.
  • the pattern classification step may include the steps comparing all the obtained results to the learning database.
  • the same tested individuals are tested biologically by Polymerase Chain Reaction (PCR) method for determination if they are healthy or infected.
  • PCR Polymerase Chain Reaction
  • all the vectors obtained by the mathematical process and the variations (i.e. the mathematically calculated differences) between the samples are "translated" to infected determination and differentiation into two groups (infected and healthy samples).
  • the system distinguishes between COVTD-19 infected and healthy individuals by measuring volatile compounds (VCs, organic or inorganic) and/or aerosols in the exhaled breath of said individuals, enabling non-invasive detection of infected or healthy individuals.
  • volatile compounds VCs, organic or inorganic
  • VCs and/or aerosols are adsorbed onto the membranes.
  • the "loaded" membranes are then analyzed by applying electromagnetic radiation (e.g., between 600-750 mih in the case of the terahertz part of the spectrum, though other bands of the electromagnetic spectrum may be used) to the membrane and observing the change in the electromagnetic radiation.
  • Analysis of the membrane may be accomplished using an electromagnetic radiation transmitter and an electromagnetic radiation detector typical of a spectrometer operating at terahertz wavelengths. During analysis the membrane is positioned within the beam of electromagnetic radiation emitted by the transmitter. The electromagnetic radiation passes into the membrane and the interaction of the VCs and/or aerosols trapped in the membrane alter the electromagnetic radiation.
  • the altered electromagnetic radiation is captured by the electromagnetic radiation detector.
  • the changes in the electromagnetic radiation can be used to determine what VCs and/or aerosols are being released in the breath of the tested individuals. By analyzing the type and amount of VCs and/or aerosols, either infected or healthy tested individuals can be determined.
  • Electromagnetic radiation in the terahertz range may be used to analyze VCs and/or aerosols.
  • the analysis spectra may be generated using absorbance, transmittance, reflectance, or Raman spectroscopy.
  • terahertz electromagnetic radiation is used for the detection of VCs and/or aerosols captured in a membrane.
  • terahertz electromagnetic radiation refers to radiation having a wavelength of between 1 mm to 0.01 mm.
  • terahertz radiation within the 600-750 mih range is used to determine the VC content in a PET or open-cell foam-based melamine membrane.
  • the electromagnetic radiation detector generates an absorption spectrum. Absorption spectra can be obtained in the frequency domain, or in the time domain and translated to frequency via Fourier transform, depending on the spectroscopic method used.
  • the absorption spectra is read and compared to a database via software matching algorithms.
  • the database contains spectral fingerprints of a healthy individual and an infected one.
  • the software matching algorithm compares the collected spectrum to the catalogued fingerprint within pre- determined confidence bounds, and identifies an COVTD-19 infected or free (healthy) individual by determining whether or not the read spectrum falls within the error bounds of the fingerprint.
  • membranes may be recycled via application of electricity to release the VCs and/or aerosols from the membrane. The "cleaned" membrane is cycled back into place on the sampling apparatus.
  • the membrane can be cleaned by reversing the flow of the vacuum motor, which causes air to pass through the membrane and push the absorbed molecules from the membrane.
  • each membrane may be used only once and then replaced by a new membrane.
  • the membranes are single used; alternatively, the membrane are cleaned and reused.
  • the device includes a gas collection device which is placed proximate to the membrane to collect the VCs and/or aerosols exhaled from the breath of the tested individuals.
  • the system will inform the user, by means of optical illustration, voice or any other means, if sufficient enough of air is exhaled and analysis can begin.
  • the system can have a red light if there is not enough of VCs and/or aerosols (from the exhaled air) and a green light is the is.
  • the membrane can be analyzed using techniques set forth herein to determine the VC content of the gas (by means of analyzing the spectrum, as described above).
  • the inventors of the present invention found that each mix or blend of VCs and/or aerosols has a separate THz signature which can be translated by using the teachings of the present invention to distinct peaks of the Fourier transformation. Therefore, the identification of the special features of the pattern such as the number of peaks, the distance between the main peaks, the identification of main and side peaks, the width of the peaks enables to define and identify a healthy individual from an infected one.
  • the inventors have found that obtaining a ratio between the THz signatures of different individuals being tested properties enables identification of these properties, and that the specific identification of each VC component as well as each concentration is not necessary to identify a healthy or a COVTD-19 infected individual.
  • the volatiles will be not only Ketones but a mixture of Ketones and/or , 1 -butanol, dimethyl disulfide, methyl benzene, hexanal, phenylethane, heptanal, benzaldehyde, dimethyl trisulfide, phenol, 2-(2-ethoxyethoxy)ethanol, 2-ethyl- 1-hexanol, 5-isopropenyl-l -methyl- 1 cyclohexene, acetophenone, 2-nonanone, 2-decanone, 2- isopropylphenol, benzothiazole, 2-undecanone, 1,3-diacetylbenzene, diethyl phthalate, 1,3-diphenyl propane, Ammonia, Greenhouse gases selected from Water vapor Methane (CH4), Carbon dioxide (C02), Nitrous oxide (N20), Ozone (03), Chlorofluorocarbons (CFCs),
  • NNA Neural Network Analysis
  • DB database
  • LEO Leave One Out
  • LOO is a statistical method used to evaluate the efficacy of any classification procedure, with a relatively low number of samples, in order to teach and train spectroscopy systems to analyze spectral vectors.
  • the training is performed repeatedly, each time after excluding one training sample from the training data of the group, and then testing on those individual vectors that were excluded from training. Based on that specific learning process of LOO, a prediction is made for the left-out spectra and compared to the actual PCR results.
  • each spectral vector is made by either using a linear classification method (see Fisher R.A. The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics, 7 Part II: 179-188, 1936) or using the Mahalanobis distance classifier (see Mahalanobis, P.C. On the generalized distance in statistics. Proceeding of the National Institute of Sciences of India. 2(1):49:55). Both methods use the classes' means and covariances to assign each input vector to its own class based on its multi- dimensional distances from each class. Therefore, the results obtained clearly indicate that this procedure is adequate for classifying unseen spectra into their associated classes, with a high probability of detection and low “false-alarm” rates.
  • the method is based on a "Principal Component Analysis” (see Konstantinos, I.D. and Sun-Yuang, K. Principal Component Neural Networks: Theory and Applications. Wiley-Inter-science, New York, 1996).
  • the mean symbol below as “m”
  • the covariance symbol below as small sigma as standard deviation
  • This procedure is essentially a linear transformation of the normalized spectra into a set of vectors that best represent the training samples and are less prone to noise.
  • eigen-vectors also called feature vectors
  • These eigen-vectors are then used to obtain a set of co-efficient vectors, one for each input spectrum, whose length equals the number of the feature vectors selected.
  • J is the power of separation between two groups
  • ml and m2 are the means of each group
  • s ⁇ and s2 are the standard deviations of each group
  • the two groups are on a continuous measurement
  • m2 the value of ml at one standard deviation.
  • the purpose of the spectral classification stage is to train the algorithm, by using a known set of spectra and then to classify previously unseen spectra into their respective classes, with a minimal number of errors.
  • the target for 100% separation is J>19 (as shown in the equation above).
  • the membrane is made of hardened extruded plastic, containing pores of two specific sizes, and acting as Ketones trap.
  • the compound could also be , 1 -butanol, dimethyl disulfide, methyl benzene, hexanal, phenylethane, heptanal, benzaldehyde, dimethyl trisulfide, phenol, 2-(2- ethoxyethoxy)ethanol, 2-ethyl- 1 -hexanol, 5-isopropenyl- 1 -methyl- 1 cyclohexene, acetophenone, 2-nonanone, 2-decanone, 2-isopropylphenol, benzothiazole, 2-undecanone, 1,3-diacetylbenzene, diethyl phthalate, 1,3-diphenyl propane, Ammonia, Greenhouse gases selected from Water vapor Methane (CH4), Carbon dioxide (C02), Nitrogene, ethylene glycol, ethylene glycol,
  • According to another embodiment of the present invention is to provide a single- use, disposable membranes. According to another embodiment the membrane is reusable.
  • the sampler (which will be integrated into a system for label-free, noncontact, noninvasive, and nondestructive detection of at least one virus infected or free (healthy) individuals from at least one tested individual), comprising a proximal end and a distal end interconnected by a main longitudinal axis, along which at least one metamaterial membrane absorber (34, see Fig. 2) is positioned; and into which said tested individual exhale breath, such that the propagation path of said exhaled breath and volatile compounds, VCs, and/or aerosols therewithin intersect said at least one metamaterial membrane and absorbed therewithin.
  • the exhaled air enters the sampler at 20 and exits at 21.
  • a membrane housing also refers to as a membrane holder
  • the sampler comprises 2 parts, a proximal part 102 and a distal part 101 interconnected by a main longitudinal axis. Said distal part is adapted to be placed in proximity to the testes subject mouth (for receiving the exhaled breath).
  • Said sampler is characterized by 2 configurations, an open configuration (shown in Fig. lb) in which the distal and proximal part are disconnected and the membrane (along with the membrane housing can be inserted or extracted from the sampler; and a closed configuration (shown in Fig. lc) in which the distal and proximal part are connected and the sampler can be used.
  • metamaterial membrane absorber 30 being configured and operable for trapping the collected volatile compounds and/or aerosols within the exhaled breath.
  • the metamaterial membrane absorber 30 is enclosed within a membrane housing 33 (see Figs. 2a-b).
  • the sampler is polyoxymethylene-based (aka DelrinTM).
  • the metamaterial membrane 34 is made of open-cell foam-based melamine.
  • the membrane housing 33 is made of PTFE (Polytetrafluoroethylene, aka Teflon).
  • PTFE Polytetrafluoroethylene, aka Teflon.
  • the membrane housing comprising a body 33 made of PTEE.
  • the membrane 34 (enclosed within the membrane housing 33) is extracted from the sampler and place in a dedicated capsule 31.
  • the dedicated capsule 31 (shown in Fig. 2) comprises a scanner holder alignment slot 32 (that ensures the correct alignment of the capsule 31 in the scanning system).
  • the capsule 31 is made of PTFE (Polytetrafluoroethylene, aka Teflon).
  • the capsule has sealing means to seal the capsule once the membrane (and the membrane housing) is inserted therein.
  • the sealing member is an o-ring.
  • the scanner holder alignment slot 32 is aligned with a protrusion in the scanner, 43 to ensure the proper alignment.
  • the scanning system comprises at least one Tx (transmitter) photomixer 41 and at least one Rx (receiver) photomixer 42 to transmit and received THz signal, respectively.
  • FIGs. 3b-3n illustrates the method of using the sampler to test individuals for SARS-CoV-2, according to the following exemplary process.
  • the membrane in inserted into the membrane holder and both are inserted into the sample (the hand-held polyoxymethylene-based tube), (see Figs. 3b-3d);
  • a tested subject receives a disposable testing kit which comprises (a) a disposable, hand-held polyoxymethylene-based (aka Delrin) tube (the sampler); (b) a disposable membrane (e.g., an open-cell foam-based melamine membrane) placed in a PTFE (Polytetrafluoroethylene, aka. Teflon) disposable holder (both the membrane and the membrane holder a pre-placed in the tube); and, (c) a disposable, sterile PTFE (Polytetrafluoroethylene, aka. Teflon) capsule.
  • the disposable testing kit is identifiable with a QR/barcode assigned to each tested subject, see Fig 3f.
  • the tested subject blows into the disposable, hand-held tube (the sampler) 3-5 prolonged breaths. See Fig. 3g;
  • the breath aerosols are absorbed onto the membrane.
  • the sampler (hand-held polyoxymethylene-based tube) is opened to enable the extraction of the membrane and its holder, see Fig. 3h;
  • the membrane (with its holder) is inserted into the capsule, see Figs. 3j- 3 k. Once the membrane (and the membrane holder) is in the capsule, the capsule is closed (thus, sealed), see Figs. 31-3m.
  • the capsule is placed inside the THz scanner and then scanned, see Fig. 3n.
  • the used capsules containing the biologically contaminated membrane (i.e., with the tested subject’s biological breath sample), will be thrown into the biological waste collection bin within the designated testing site.
  • the THz scanner virus is a THz sensing spectrometer, in the range of 0.3 THz to 30 THz operated as a diagnostic molecular radar.
  • the THz scanner main parts are 2 Distributed Feedback Faser, DFB lasers, temperature electric control units, control unit, power unit and photo mixers.
  • the laser beam is used to modulate a photocurrent at a tuned THz frequency by illuminating the TX photo mixer, the THz beam travel through the Sample Under Test (SUT) and received at the RX photo mixer.
  • SUT Sample Under Test
  • Figs. 4a-4d illustrates another embodiment of the sampler.
  • the sampler is composed of 2 parts as seen in Figs. 4a-4b.
  • the tested individual exhales air (the arrows in Fig. 4b denotes the air movement). Thereafter, the two parts are assembled together (by approaching one to the other), see Fig. 4c and taken by a dedicated tool (illustrated in Fig. 4d) to be scanned by the THz scanner.
  • FIGs. 5a-5b showing a sampler in which the membrane and the membrane housing are already integrated therewithin.
  • the sampler is then closed and sealed and then scanned in the THz domain. Thus, no need for extraction of the membrane from the sampler to the capsule.
  • the sampler has a body 51, an upper portion 52 insertable into the tested subject’s mouth (for exhale breath) and a lower portion 53. After the subject exhale breath the sampler is sealed by means of 54 and 55 closures closing the upper and lower portions (see arrows 56 and 57).
  • Closures 54, 55 both close the sampler and seal the same.
  • Fig. 5b illustrates a cross sectional view of the sampler.
  • the membrane (and the membrane housing) are placed in location 58.
  • Fig. 5c illustrates another embodiment of the sampler, in which at least one of the closures is spiral -like coupled to the body of the sampler.
  • FIG. 5d-5e illustrates a cross sectional view of Fig. 5d.
  • the sampler is made of 2 parts 61 and 62. Each part is composed of a body and a closure 63 and 64, respectively.
  • the membrane 66 Prior to coupling the two parts, the membrane 66 (or membrane housing) is placed. Once the membrane is positioned at its location (see Fig. 5h), the sampler is ready for use.
  • FIG. 5i illustrating another embodiment of the present invention, in which the closures 54 and 55 are provided as separate parts and not as integral part of the sampler.
  • FIGs. 6a-6f illustrating another embodiment of the present invention, in which the sampler 500 additionally comprising Lego-like connection(s) (71 and 72) are provided so as to enable stack like connection between the sampler prior to insertion into the THz scanner (as discussed below).
  • the THz scanner virus is a THz sensing spectrometer, in the range of 0.3 THz to 30 THz operated as a diagnostic molecular radar.
  • the THz scanner main parts are 2 Distributed Feedback Laser, DFB lasers, temperature electric control units (temperature controllers), a control unit (controller), power unit and photo mixers.
  • the laser beam is used to modulate a photocurrent at a tuned THz frequency by illuminating the TX photo mixer, the THz beam travel through the Sample Under Test (SUT) and received at the RX photo mixer.
  • a controller 106 of at least one embodiment is configured to receive and process signals from a sample and identify spectral special features indicative of the sample.
  • the THz signature may include information on the virus status of the individual.
  • the controller 106 is configured and operable for performing a pattern recognition of the THz signature.
  • the control unit 106 is configured generally as a computing/electronic device including inter alia such utilities as data input and output utilities 106A, 106B, memory (e.g., non-volatile memory) 106C, and data processing utility (e.g. data processor) 106D.
  • the utilities of the control unit 106 may thus be implemented by suitable circuitry and/or by software and/or hardware components including computer readable code configured for implementing the operations of methods and systems described herein.
  • Figs. 4-4d illustrates another embodiment of the sampler.
  • the sampler is composed of 2 parts.
  • FIG. 5-6 illustrating alternative embodiments of the sampler device. In those embodiments, the use of a capsule is redundant.
  • the sampler has a body 51, an upper portion 52 insertable into the tested subject’s mouth (for exhale breath) and a lower portion 53. After the subject exhale breath the sampler is sealed by means of 54 and 55 closures closing the upper and lower portions (see arrows 56 and 57).
  • Closures 54, 55 both close the sampler and seal the same.
  • Fig. 5b illustrates a cross sectional view of the sampler.
  • the membrane (and the membrane housing) are placed in location 58.
  • Fig. 5c illustrates another embodiment of the sampler, in which at least one of the closures is spiral -like coupled to the body of the sampler.
  • FIG. 5d-5e illustrates a cross sectional view of Fig. 5d.
  • the sampler is made of 2 parts 61 and 62. Each part is composed of a body and a closure 63 and 64, respectively.
  • the membrane 66 Prior to coupling the two parts, the membrane 66 (or membrane housing) is placed. Once the membrane is positioned at its location (see Fig. 5h), the sampler is ready for use.
  • FIG. 5i illustrating another embodiment of the present invention, in which the closures 54 and 55 are provided as separate parts and not as integral part of the sampler.
  • FIGs. 6a - 6f illustrating another embodiment of the present invention, in which the sampler 500 additionally comprising Lego-like connection (71 and 72) are provided so as to enable stack like connection between the sampler prior to insertion into the THz scanner (will be illustrated herein below).
  • the sampler 500 comprises closures 63 and 64 where closure 64 is provided to the mouthpiece part 68 (adapted to be inserted into the subject’s mouth) and closure 63 is provided to the distal most part 69 (from which the exhaled breath exits). Both closures 63 and 64 when closing the sampler are adapted to seal the same.
  • the sampler comprises a narrower portion 67 within the mouthpiece part 68. Said narrower portion 67 is provided so as to focus the exhaled breath to the membrane 66.
  • the sampler comprises a cross-like portion 74 upon which the membrane 66 is placed on.
  • the positioning of the membrane 66 on the cross-like portion 74 results in an air flow 73 (see Fig. 6c) of the exhaled breath to reach the membrane (and absorbed therewithin) and to exit the sampler, mostly from the sideways thereof (see Fig. 6d).
  • the integrated system comprises a THz generator module (generator) and the THz scanner (into which the samplers 500 are entered to be scanned).
  • Fig. 6g illustrates the THz system and the stacked samplers entering therewithin.
  • the integrated system will also enclose a waste container to enclose all the used samplers containing the biological sample.
  • Figs. 6h-6i illustrate the THz scanner and the samplers 500 entering thereto.
  • the samplers are placed on a conveyor 501 powered by an engine 502.
  • a camera 503 is optionally disposed therewithin to ensure the movement of the samplers 500 on the conveyor to their correct portioning in between the THz transceiver and the THz receiver (photo-mixer 504).
  • Figs. 6j-6o illustrates another embodiment of the sampler.
  • the membrane is inserted into the sampler, then (see Fig. 6k) the mouthpiece is placed.
  • Figs. 9a-9m illustrate performance of the sampler shown e.g., in Fig. 6a and described above.
  • Fig. 9a illustrates a direction of air flow in the sampler according to an exemplary embodiment.
  • the pressure drop and centered VOC accumulation were simulated.
  • the inlet flow simulation was intended to comport with the average adult exhalation, with an average exhalation air volume of 1.1 L.
  • a membrane was used in the simulation having a density of 8-16 kg/m A 3.
  • the average velocity flow into the sampler was 9.75 m/s.
  • the membrane density range in at least one simulation was 9 kg/m A 3 and the foam diameter was 14 mm.
  • the pressure out was 1 atm.
  • Table 1 Tested volume and air speed [0644] The amount of volume of an average human exhalation was tested by inflating a balloon.
  • Fig. 9b depicts a simulation utilizing the sampler (the breathalyzer) of the at least one embodiment where the thickness of the foam tested was 5 mm, and the velocity of the inlet air (i.e., the exhaled air) was about 28 m/s.
  • Fig. 9n depicts contour plots for the simulation in Fig. 9b with respect to cross-sections zl, z2, z3 and z4 (discussed in more detail with respect to Fig. 9i).
  • Fig. 9e depicts a velocity simulation of the inlet air (i.e., the exhaled air), where the maximum velocity had reached 9.75 m/s, where the thickness of the foam tested was 5 mm.
  • Fig. 9g depicts a velocity simulation for conditions the same as 9f of no membrane, but with a barrier present. The maximum velocity of the inlet air (i.e., the exhaled air) was calculated to be at 9.75 m/s.
  • Fig. 9p depicts a velocity simulation for conditions the same as Fig. 9o, where the velocity of the inlet air (i.e., the exhaled air) was at 9.75 m/s.
  • Fig. 9q depicts pressure contour plots for the pressure simulation of Fig. 9o.
  • Fig. 9p depicts a velocity simulation for conditions the same as Fig. 9o, where the velocity of the inlet air (i.e., the
  • FIG. 9s depicts a velocity simulation for conditions the same as 9r, where the velocity of the inlet air (i.e., the exhaled air) was at 9.75 m/s.
  • Fig. 9h depicts the pressure Pa as a function of distance (x mm) in the axial direction of the sampler. As can be seen, the maximum pressure change is at the membrane, gradually decreasing to the exit side of the sampler (the breathalyzer).
  • Fig. 9i depicts representative cross-sections (z0-z4) of the membrane at different ‘depth’ within the same; and shows the radius of the inner cross section of the sampler from a center thereof.
  • Fig. 9j depicts pressure Pa as a function of different locations along the radius of the sampler at cross section zl of the membrane.
  • Fig 9k depicts pressure as a function of different locations along the radius at cross section z2 of the membrane.
  • Fig. 91 depicts pressure as a function of different locations along the radius at cross section z3 of the membrane.
  • Fig. 9m depicts pressure as a function of different locations along the radius at cross section z4 of the membrane.
  • z4 which is a position at the distal most end of the membrane
  • Fig. 7, illustrating an embodiment in which the membrane housing 30 is integrated in the sampler and provided as a kit with an RFID tag 51 or barcode 52.
  • Said RFID tag 51 or barcode 52 are identifiable to each tested. Such that when the results are provided, only the tested individual the results pertain to can review the results. It also ensures no identity mistakes are made.
  • IL interleukin
  • IL-7 interleukin-2 receptor
  • IL-6 interleukin-6
  • SSPPs spoof surface plasmon polaritons
  • sampler is RFID tagged with each of said tested individual, such that detection of said virus infected individuals is traced back to each of said tested individual.
  • sampler is a disposable unit;
  • sampler comprises at least one sealing element adapted to seal thereof.
  • control unit is configured and operable for performing a pattern recognition of said signature.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus infected individuals.
  • a radiation transmitter unit being configured and operable to scan said permeable membrane holding the collected volatile compounds and/or aerosols by generating an electromagnetic radiation in the range of THz within a scanning window of about 100 GHz
  • a detection unit being configured and operable to detect an electromagnetic radiation emitted by said collected volatile compounds and/or aerosols.
  • At least one electromagnetic testing unit comprising at least one electromagnetic radiation transmitter and at least one electromagnetic radiation detector; said membrane, after absorbing said volatile compounds and/or aerosols, being positionable within the electromagnetic radiation emitted by said at least one transmitter; such that said electromagnetic testing unit adapted to (a) scan in the THz range said metamaterial membrane absorbed with said volatile compounds and/or aerosols in said exhaled breath of said tested individual; and, (b) transmit data indicative of the collected volatile compounds and/or aerosols to said control unit;
  • control unit configured and operable for receiving data indicative of the collected volatile compounds and/or aerosols from said electromagnetic testing unit and processing said data for identifying a signature being indicative of virus infected individuals to thereby provide detection of said virus infected individuals.
  • IL interleukin
  • IL-7 interleukin-2 receptor
  • IL-6 interleukin-6
  • SSPPs spoof surface plasmon polaritons
  • control unit is configured and operable for performing a pattern recognition of said signature.
  • control unit trains a machine learning model to detect at least one parameter in the absorption spectrum of said membrane with said collected volatile compounds and/or aerosols being scanned with an electromagnetic radiation in the THz range of a plurality of membrane stored in said communicable and readable database in order to generate information data being indicative of said virus infected individuals.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit detects said signature the absorption spectrum of said membrane with said VCs and/or aerosols being indicative of at least one said virus infected individuals by means of said trained machine learning model.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus infected individuals.
  • CH4 Water vapor Methane
  • C02 Carbon dioxide
  • a radiation transmitter unit being configured and operable to scan said permeable membrane holding the collected volatile compounds and/or aerosols by generating an electromagnetic radiation in the range of THz within a scanning window of about 100 GHz
  • a detection unit being configured and operable to detect an electromagnetic radiation emitted by said collected volatile compounds and/or aerosols.
  • a control unit configured and operable for receiving data indicative of the collected volatile compounds and/or aerosols being scanned with an electromagnetic radiation in the THz range and processing said data for identifying a signature being indicative of virus infected individuals to thereby provide detection of said virus infected individuals.
  • sampler as defined above, wherein at least one of the following us being held true (a) said sampler is a disposable unit; (b) said sampler comprises at least one sealing element adapted to seal thereof.
  • said signature is information indicative of said virus; said information being selected from a group consisting of cell unit of said virus, viral proteins, cellular debris, debris of said virus, hydrates of said virus, hydrates of debris of said virus, hydrates of the 3D structure of said virus and a cell, aggregates of said virus, cytokines, increased level of interleukin (IL)-2, interleukin IL-7, interleukin-2 receptor (IL-2R), interleukin-6 (IL-6), granulocytecolony, stimulating factor, interferon-g, inducible protein 10, monocyte chemoattractant, protein 1, macrophage, inflammatory protein 1-a, and tumor necrosis factor-a, and any combination thereof.
  • IL interleukin
  • IL-7 interleukin-2 receptor
  • IL-6 interleukin-6
  • SSPPs spoof surface plasmon polaritons
  • aid parameter selected from a group consisting of, trends in said database of said at least one tested individuals, eigenvector of said database of said at least one tested individuals
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus infected individuals.
  • a radiation transmitter unit being configured and operable to scan said permeable membrane holding the collected volatile compounds and/or aerosols by generating an electromagnetic radiation in the range of THz within a scanning window of about 100 GHz
  • a detection unit being configured and operable to detect an electromagnetic radiation emitted by said collected volatile compounds and/or aerosols.
  • IL interleukin
  • IL-7 interleukin-2 receptor
  • IL-6 interleukin-6
  • SSPPs spoof surface plasmon polaritons
  • said virus is selected from a group selected from COV viruses family, COVID- 19, Influenza, Avian influenza and any combination thereof.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus infected individuals.
  • IL interleukin
  • IL-7 interleukin-2 receptor
  • IL-6 interleukin-6
  • SSPPs spoof surface plasmon polaritons
  • said sampler is airtight sealed such that said volatile compounds, VCs, and/or aerosols released by said at least one tested individuals breath are prevented from exiting said sampler.
  • said electromagnetic testing unit comprising at least one electromagnetic radiation transmitter and at least one electromagnetic radiation detector.
  • the membrane is positionable within the electromagnetic radiation emitted by the transmitter.
  • said control unit is configured and operable for performing a pattern recognition of said signature.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus infected individuals.
  • a spectroscopic assembly including a radiation transmitter unit being configured and operable to scan said permeable membrane holding the collected volatile compounds and/or aerosols by generating an electromagnetic radiation in the range of THz within a scanning window of about 100 GHz and a detection unit being configured and operable to detect an electromagnetic radiation emitted by said collected volatile compounds and/or aerosols.
  • SSPPs spoof surface plasmon polaritons
  • T It is another object of the present invention to provide the method as defined above, wherein said virus is selected from a group selected from COV viruses family, COVID- 19, Influenza, Avian influenza and any combination thereof.
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • LEO Leave One Out
  • NNA Network Acceleration algorithm
  • control unit additionally performs Fast Fourier Transformation in order to generate information data being indicative of said virus infected individuals.
  • the THz spectrum collected from scanning the membraned with the tested subject’s exhaled breath is calibrated or normalized with at least one parameter.
  • the parameter can be any (or all) of the following PCR Ct, temperature at the location where the sample had been taken, humidity at the location where the sample had been taken, barometric pressure at the location where the sample had been taken, the relative position of one THz scanner to another one, the location at which said sample is taken, a THz scan of a predefined gold standard and any combination thereof.
  • the predefined gold standard could be a non- used membrane, a non Covid-19 infected subject (i.e., a healthy subject), a Covid-19 infected subject (i.e., a Covid-19 sick subject).
  • compositions, method or structure may include additional ingredients, steps and/or parts, but only if the additional ingredients, steps and/or parts do not materially alter the basic and novel characteristics of the claimed composition, method or structure.
  • the singular form “a”, “an” and “the” include plural references unless the context clearly dictates otherwise.
  • the term “a compound” or “at least one compound” may include a plurality of compounds, including mixtures thereof.
  • a numerical range is indicated herein, it is meant to include any cited numeral (fractional or integral) within the indicated range.
  • the phrases "ranging/ranges between” a first indicate number and a second indicate number and “ranging/ranges from” a first indicate number “to” a second indicate number are used herein interchangeably and are meant to include the first and second indicated numbers and all the fractional and integral numerals therebetween.
  • the term “method” refers to manners, means, techniques and procedures for accomplishing a given task including, but not limited to, those manners, means, techniques and procedures either known to, or readily developed from known manners, means, techniques and procedures by practitioners of the chemical, pharmacological, biological, biochemical and medical arts.
  • the term “treating” includes abrogating, substantially inhibiting, slowing or reversing the progression of a condition, substantially ameliorating clinical or aesthetical symptoms of a condition or substantially preventing the appearance of clinical or aesthetical symptoms of a condition.
  • IBV233A Infectious Bronchitis Virus, an avian corona virus
  • strain IBVR233A
  • IBV233A was diluted is double distilled water (DDW) as per manufacturer guidelines, (1 capsule dissolved in 30mL DDW results in ⁇ 10 ⁇ 4 virions per mL, (i.e., stock solution, marked as triangles in Figs. 8a-8b).
  • the stock solution was further diluted 1:10 in DDW to produce the following concentrations: xlOOO, ( — 10 ⁇ 3 virions/ mL), XI 00, ( ⁇ 10 ⁇ 2 virions/mL), and XI 0, ( ⁇ 10 virions/mL) .
  • Membrane denoted in the Fig. as ‘ Ref ) alone and vehicle control were tested as well, Ref (i.e., the membrane) and Ref soaked in water samples, all illustrated in Figs. 8a-c.
  • FIGs. 8a-c illustrate clustering analysis of the Avian Corona Virus results. As clearly illustrated in Figs. 8a-b, the clustering yielded distinct groups, suggesting that each being characterized by different spectral signatures.
  • the first sample included healthy) Covid-19 free) subjects with no symptoms and confirmed (infected) Covid-19 patients from the Isolation Unit at The Sheba Medical Institute.
  • our clustering analysis resulted in a definite two group separation for Healthy versus Infected subjects, (circles refers to the Covid-19 free individuals, and circles with ‘x’ therewithin refers to the covid-19 infected individuals).
  • Fig. 8f illustrates healthy (Covid-19 free) subjects showing no symptoms, Covid- 19 recovered subjects showing no symptoms and Covidl9 infected subjects showing symptoms.
  • Fig. 8h illustrates clustering analysis of healthy (Covid-19 free) subjects and infected subjects, taken at different time frames at different locations.
  • two distinct groups are identified by a proprietary analysis: denoted in the Figure as circles with ‘x’ therewithin, top of the Figure) which resembles healthy subjects, and Mixed shapes, (bottom of the Figure), which resembles covid-19 infected subjects, as taken at different time frames.
  • Fig. 8i breath samples were collected from patients admitted to the ER for infection categorized other than covid-19, (denoted as circles in the above illustration, Fig. 8i) and infected ones. Notably the latter group fall into the "healthy group", (left of the border), using our clustering analysis, thus distinguishing health (Covid- 19 free) subjects from infected ones.
  • the results of this analysis are illustrated in Fig. 8j below.
  • Fig. 8j illustrates classification of ER admissions versus know healthy patients and known Covid-19 patients.
  • Fig. 8k illustrates is a correlation analysis which reveals a unique spectral features to covid-19 patients. Note the peaks 450 and 920 GHz, which are unique to Covid-19 infected subjects.
  • patient information was gathered including presence or absence of various comorbidities.
  • the RT-PCR sample was collected and the tube containing the collection swab was identified with the patient's unique ID label.
  • the blow sample was collected by blowing five times in the disposable collection tube and the unique ID label of the disposable breath analyzer kit was applied to this kit and also to the tube containing the RT-PCR collection swab.
  • the patient pool was as follows:
  • Table 3 Number of symptomatic and asymptomatic patients
  • the minimum age of the patients was 18 years and the maximum age was 89 years.
  • the mean age was 37 years.
  • the minimum age of symptomatic patients was 18 years and the maximum age was 78 years.
  • the mean age was 37 years.
  • the minimum age of asymptomatic patients was 18 years and the maximum age was 89 years.
  • the mean age was 37 years.

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Abstract

L'invention concerne une méthode à haut rendement pour la détection sans marqueur, sans contact, non invasive et non destructive d'au moins un individu infecté par un virus ou exempt de virus par rapport à au moins un individu testé. La méthode comprend la collecte d'un échantillon de l'haleine expirée d'un sujet pour l'analyse de l'échantillon. La collecte comprend l'expiration du sujet dans au moins un échantillonneur et la collecte des aérosols et/ou de tout composé en suspension dans l'air à partir de l'haleine expirée en faisant passer l'haleine expirée à travers une membrane métamatériau à l'intérieur de l'échantillonneur. La membrane métamatériau est disposée transversalement à un flux d'haleine expirée à travers l'échantillonneur. La méthode comprend en outre l'analyse de l'échantillon pour la détection d'au moins un individu infecté par un virus parmi au moins un individu testé.
EP21771884.0A 2020-03-20 2021-03-19 Systèmes et méthodes pour la détermination non invasive de l'infection par le coronavirus covid-19 Pending EP4121760A4 (fr)

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US202062992627P 2020-03-20 2020-03-20
US202063000077P 2020-03-26 2020-03-26
US202063002404P 2020-03-31 2020-03-31
IL273709A IL273709A (en) 2020-03-31 2020-03-31 A system and method for non-invasively detection of coronoavirus (covid-19)
US202063012682P 2020-04-20 2020-04-20
US202063012672P 2020-04-20 2020-04-20
US202063015723P 2020-04-27 2020-04-27
US202063015714P 2020-04-27 2020-04-27
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US202063111089P 2020-11-09 2020-11-09
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