Chemometric analysis of chemical agents using electrochemical detection and classification techniques

• US 10,520,459 B2
• Filed: 06/07/2017
• Issued: 12/31/2019
• Est. Priority Date: 10/29/2012
• Status: Active Grant

• Current Assignee: Universitat Autonoma De Barcelona, Regents of the University of California (University of California)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Wang, Joseph, Windmiller, Joshua Ray, O'Mahony, Aoife, Ceto, Xavier, Del Valle, Manel
• Primary Examiner(s): Kaur, Gurpreet
• Assistant Examiner(s): Rosenwald, Steven E
• Application Number:
  US15/616,660
• Publication Number:
  US 20170350848A1
• Time in Patent Office: 937 Days
• Field of Search: None
• CPC Class Codes: G01N 27/307 Disposable laminated or multilayered electrodes G01N27/3272 takes precedence
• CPC Class Codes: G01N 27/48 using polarography, i.e. measuring changes in current under a slowly-varying voltage
• CPC Class Codes: G01N 33/0057 for warfare agents or explosives properties of explosives G01N33/227

Abstract

Methods, systems, and devices are disclosed for the identification of chemical agents and determination of their level of exposure using electrochemical detection and advanced signal processing. In one aspect, a method includes collecting a sample from a surface containing a chemical agent to an electrode on a sensor such that the chemical agent transfers on the electrode, detecting an electrochemical signal of the chemical agent on the electrode to transduce chemical information associated with the chemical agent to an electrical signal, processing the electrical signal to obtain electrochemical spectral signature data to identify the chemical agent and generating a series of coefficients of the electrochemical spectral signature data to reduce the data, and classifying the chemical information based on the series of coefficients among preselected data sets to determine a level of exposure to the chemical agent.

Claims

1. A chemical analysis system, comprising:

an electrode strip to collect a sample from a surface containing a chemical agent, the electrode strip including;

a substrate of an electrically insulative material,

a plurality of electrodes on the substrate forming a single electrode contingent for an electrochemical analysis, and

electrode interface contacts on the substrate and electrically coupled to the electrodes via electrically conductive conduits;

an electrochemical analysis unit structured to receive the electrode strip to transduce chemical information associated with the chemical agent to an electrical signal; and

a data processing unit in communication with the electrochemical analysis unit and structured to include one or more memory units and one or more processors configured to process the electrical signals as data to identify the chemical agent by determining an electrochemical spectral signature based on the chemical information contained in the transduced electrical signal,

wherein the data processing unit is configured to determine a level of exposure of the sample to the chemical agent by;

generating a series of coefficients of the electrochemical spectral signature to compress the data, and

classifying the chemical information based on the series of coefficients among preselected data sets to determine a level of exposure to the chemical agent, the classifying including performing pattern recognition using the preselected data sets and the series of coefficients to assign a group membership or ranking to the chemical information by maximizing inter-group variance between unique groups and minimizing intra-group variance.

2. The system as in claim 1, wherein the data processing unit generates the series of coefficients of the electrochemical spectral signature using a discrete Wavelet transform (DWT) or a fast Fourier transform (FFT).

3. The system as in claim 2, wherein the data processing unit uses the DWT or the FFT to filter noise from the electrical signal.

4. The system as in claim 1, wherein the data processing unit classifies the chemical information by using at least one of principal component analysis (PCA), analysis of variance (ANOVA), regression analysis, Fisher'"'"'s linear discriminant (FLD), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), neural networks, perceptrons, support vector machines, Bayes classifiers, kernel estimation, decision trees, maximum entropy classifier, or K-means clustering.

5. The system as in claim 1, wherein the chemical agent includes gunshot residue (GSR) or explosive residue (ER).

6. The system as in claim 5, wherein the data processing unit classifies the level of exposure to the GSR into a plurality of groups including a No Contact group, a Secondary Contact group, and a Primary Contact group.

7. The system as in claim 1, wherein the electrochemical analysis unit and data processing unit are configured in a portable device to identify the chemical agent and determine the level of exposure of the sample to the chemical agent.

8. The system as in claim 7, further comprising:

a remote computer in communication with the portable device via a communication network or link to receive the processed data including the classified chemical information from the portable device and to process the classified chemical information in a data library of previously collected samples.

9. The system as in claim 1, wherein the electrochemical analysis unit is configured in a portable device and the data processing unit is configured in a remote computer, wherein the portable device includes:

a processor and memory unit coupled to the electrochemical analysis unit, and

a transmitter unit to transmit the transduced electrical signal as transmitted data to the remote computer,

wherein the remote computer is in communication with the portable device via a communication network or link to receive the transmitted data and process the transmitted data to identify the chemical agent and determine the level of exposure of the sample to the chemical agent.

10. The system as in claim 1, wherein the single electrode contingent of the electrode strip includes (i) one working electrode and one reference electrode or (ii) one working electrode, one counter electrode, and one reference electrode.

11. The system as in claim 1, wherein the electrode strip further includes an electrically insulative layer formed over a region of the substrate between the electrodes and the electrode interface contacts.

12. An integrated electrode device to collect and analyze a sample, comprising:

a substrate of an electrically insulative material;

a plurality of electrodes of an electrically conductive material on the substrate forming a single electrode contingent for an electrochemical analysis of one or more chemical agents present in a sample collected on the integrated electrode device, wherein the single electrode contingent of the electrode strip is structured to include (i) one working electrode and one reference electrode or (ii) one working electrode, one counter electrode, and one reference electrode; and

electrode interface contacts on the substrate and electrically coupled to the electrodes via electrically conductive conduits,

wherein the integrated electrode device is operable for the electrochemical analysis when the sample is in physical contact with the working electrode and electrically coupled, via the electrode interface contacts, to an electrical circuit to transduce chemical information associated with the one or more chemical agents to an electrical signal, and wherein the electrical circuit is in communication with a data processing unit configured to process the electrical signal as data to identify the one or more chemical agents by determining an electrochemical spectral signature based on the chemical information contained in the transduced electrical signal and to determine a level of exposure of the sample to the one or more chemical agents by;

generating a series of coefficients of the electrochemical spectral signature to compress the data, and

classifying the chemical information based on the series of coefficients among preselected data sets to determine a level of exposure to the one or more chemical agents, the classifying including performing pattern recognition using the preselected data sets and the series of coefficients to assign a group membership or ranking to the chemical information by maximizing inter-group variance between unique groups and minimizing intra-group variance.

13. The device as in claim 12, further comprising:

an electrically insulative layer formed over a region of the substrate between the plurality of electrodes and the electrode interface contacts.

14. The device as in claim 12, wherein the integrated electrode device is capable of collecting the sample by swiping a surface using the surface of the electrode contingent of the device.

15. A method to identify and analyze exposure levels of a chemical agent, comprising:

collecting, at an electrode strip, a sample from a surface containing a chemical agent to an electrode of a sensor on the electrode strip to cause a contact between the chemical agent and the electrode;

detecting, at an electrochemical analysis unit, an electrochemical signal of the chemical agent on the electrode to transduce chemical information associated with the chemical agent to an electrical signal;

processing, at a data processing unit, the electrical signal to generate data to obtain an electrochemical spectral signature from the data to identify the chemical agent; and

classifying, at the data processing unit, the chemical information based on predetermined data indicating different levels of exposure to the chemical agent under different conditions to determine a level of exposure to the chemical agent from the sample,

wherein the level of exposure to the chemical agent from the sample is determined by;

generating a series of coefficients of the electrochemical spectral signature by compressing the data, and

performing pattern recognition using the predetermined data and the series of coefficients to assign a group membership or ranking to the chemical information by maximizing inter-group variance between unique groups and minimizing intra-group variance.

16. The method as in claim 15, wherein the pattern recognition includes at least one of principal component analysis (PCA), analysis of variance (ANOVA), regression analysis, Fisher'"'"'s linear discriminant (FLD), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), neural networks, perceptrons, support vector machines, Bayes classifiers, kernel estimation, decision trees, maximum entropy classifier, or K-means clustering.

17. The method as in claim 15, wherein the compressing the data to generate the series of coefficients includes using a discrete Wavelet transform (DWT) or a fast Fourier transform (FFT).

18. The method as in claim 17, further comprising, at the data processing unit, using the DWT or the FFT to filter noise from the electrical signal.

19. The method as in claim 15, wherein the collecting includes swiping the surface using the electrode surface of the sensor.

20. The method as in claim 19, wherein the sensor includes a printed three-electrode strip or a printed two-electrode strip, wherein the three-electrode strip is structured to include a working electrode, a counter electrode, and a reference electrode, and the two-electrode strip is structured to include a working electrode and a reference electrode.

21. The method as in claim 15, wherein the detecting the electrochemical signal includes performing at least one of voltammetry, cyclic voltammetry, square wave voltammetry, differential pulse voltammetry, amperometry, chronoamperometry, potentiometry, chronopotentiometry, coulometry, chronocoulometry, conductometry, or impedometry.

22. The method as in claim 15, wherein the chemical agent includes gunshot residue (GSR) or explosive residue (ER).

23. The method as in claim 22, wherein the predetermined data include a plurality of groups of differing levels of exposure to GSR including a No Contact group, a Secondary Contact group, and a Primary Contact group.

24. The method as in claim 23, wherein the Secondary Contact group includes subjects that have been present in an environment where a firearm was discharged (a) without a subject handling the firearm or (b) with the subject handling the firearm but not firing it.

25. The method as in claim 23, wherein the Primary Contact group includes subjects that have fired a firearm.

26. The method as in claim 25, wherein the Primary Contact group includes subjects that have fired the firearm and washed their hands subsequent to the firing of the firearm.