Systems, methods and devices for acquiring and processing physiological signals

• US 9,782,104 B2
• Filed: 03/26/2015
• Issued: 10/10/2017
• Est. Priority Date: 03/26/2014
• Status: Active Grant

• Current Assignee: Trenda Innovations, Inc.
• Original Assignee: GestureLogic Inc.
• Inventors: MacEachern, Leonard, Klibanov, Mark, Stupich, Nick, Etemad, Seyed Ali, Iyer, Niranjan, Straka, Adrian
• Primary Examiner(s): MALAMUD, DEBORAH LESLIE
• Application Number:
  US14/669,781
• Publication Number:
  US 20150272501A1
• Time in Patent Office: 929 Days
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0531 Measuring skin impedance
• CPC Class Codes: A61B 5/0537 Measuring body composition by impedance, e.g. tissue hydration or fat content
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4875 Hydration status, fluid retention of the body
• CPC Class Codes: A61B 5/6823 Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: A61B 5/6824 Arm or wrist
• CPC Class Codes: A61B 5/6828 Leg
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A system, method and device are described for biometric analysis using a wearable device. The device can be removeably securable to a user'"'"'s skin surface and can include a plurality of electrodes positioned to acquire electrical signals from the skin surface. The device can also include an electromyography acquisition module and skin impedance acquisition module. A processing unit can use the electrodes to capture a plurality of electrical signals including at least one electromyography signal. The processing unit can generate calibration data based on a subset of the captured electrical signals and process the electromyography signals using the calibration data to determine a biometric for the user.

Claims

1. A biometric analysis system comprising:

a remote processing device; and

a wearable device, the wearable device removeably securable to a user skin surface with a skin-facing surface of the wearable device positioned to make contact with the skin surface, the wearable device having;

a plurality of electrodes positioned to acquire an electrical signal from the skin surface;

a controller;

a signal acquisition unit operatively coupled to the controller and to the plurality of electrodes, the signal acquisition unit having a skin impedance acquisition module and an electromyography acquisition module; and

a wireless communication module operatively coupled to the controller to communicate with the remote processing device; and

at least one of the controller and the remote processing device is configured to;

cause the injection of at least one precursor signal into at least one of the plurality of electrodes;

capture, via the signal acquisition unit and the plurality of electrodes, a plurality of electrical signals comprising at least one electromyography signal and at least one impedance signal based on the at least one precursor signal;

generate calibration data based on the at least one impedance signal; and

process the at least one electromyography signal using the calibration data to determine at least one biometric.

2. The system of claim 1, wherein:

the at least one impedance signal comprises at least one skin impedance signal; and

the subset of the plurality of electrical signals used to generate the calibration data comprises the at least one skin impedance signal.

3. The system of claim 1, wherein the at least one biometric comprises at least one of muscle intensity, muscle coordination, muscle ratio, and fatigue.

4. The system of claim 1, wherein the wearable device further comprises at least one of an inertial measurement unit and a GNSS unit.

5. The system of claim 1, wherein each electrode is a passive electrode.

6. The system of claim 5, wherein the signal acquisition unit further comprises a bio-impedance acquisition module.

7. The system of claim 6, wherein the signal acquisition unit further comprises:

a primary multiplexer module; and

the signal acquisition unit is coupled to the plurality of electrodes using the primary multiplexer module.

8. The system of claim 7, wherein the signal acquisition unit further comprises:

the primary multiplexer module coupled to the plurality of electrodes; and

a secondary multiplexer module coupled to the primary multiplexer module;

wherein each of the skin impedance acquisition module and the bio-impedance acquisition module is coupled to the primary multiplexer module by the secondary multiplexer module; and

the electromyography acquisition module is coupled directly to the primary multiplexer module.

9. The system of claim 5, wherein the wearable device further comprises:

an analog to digital converter coupled to the controller; and

each of the skin impedance acquisition module, the bio-impedance acquisition module, and the electromyography acquisition module are coupled to the controller by the analog to digital converter.

10. The system of claim 9, wherein each of the skin impedance acquisition module, the bio-impedance acquisition module, and the electromyography acquisition module provide unprocessed signals to the analog to digital converter.

11. The system of claim 10, wherein the electromyography acquisition module has an amplifier that amplifies the electromyography signal prior to providing the electromyography signal to the analog to digital converter.

12. The system of claim 1, wherein the remote processing device is a mobile device.

13. The system of claim 1, wherein the remote processing device comprises a display, and the remote processing device is configured to display feedback based on the at least one biometric.

14. The system of claim 13, wherein the feedback comprises at least one of a report on the at least one biometric and a visualization of the at least one biometric.

15. The system of claim 1, further comprising:

a cloud server having a cloud storage module that stores a user profile associated with the wearable device, wherein the user profile includes a historical record of the at least one biometric.

16. The system of claim 15, further comprising:

a plurality of wearable devices; and

wherein the cloud storage module stores a unique user profile for each user in a plurality of users, and each wearable device is associated with one of the unique user profiles.

17. The system of claim 1, wherein the wearable device further comprises an alignment guide for aligning the wearable device with a desired region of the skin surface.

18. The system of claim 1, wherein each electrode is an active electrode.

19. The system of claim 1, wherein:

the at least one impedance signal comprises at least one bio-impedance signal; and

the subset of the plurality of electrical signals used to generate the calibration data comprises the at least one bio-impedance signal.

20. A wearable device for biometric analysis, the device comprising:

a skin-facing surface removeably securable to a user skin surface, with the skin-facing surface positioned to make contact with the skin surface;

a plurality of electrodes positioned to acquire an electrical signal from the skin surface;

a controller; and

a signal acquisition unit operatively coupled to the controller and to the plurality of electrodes, the signal acquisition unit having a skin impedance acquisition module and an electromyography acquisition module;

the controller configured to;

cause the injection of at least one precursor signal into at least one of the plurality of electrodes;

capture, via the signal acquisition unit and the plurality of electrodes, a plurality of electrical signals comprising at least one electromyography signal and at least one impedance signal based on the at least one precursor signal;

generate calibration data based on the at least one impedance signal; and

process the at least one electromyography signal using the calibration data to determine at least one biometric.

21. A method for biometric analysis using a wearable device positioned to make contact with a skin surface of a user, the wearable device having a plurality of electrodes positioned to acquire an electrical signal from the skin surface, the method comprising:

causing the injection of at least one precursor signal into at least one of the plurality of electrodes;

capturing, via the signal acquisition unit and the plurality of electrodes, a plurality of electrical signals comprising at least one electromyography signal and at least one impedance signal based on the at least one precursor signal;

generating calibration data based on the at least one impedance signal; and

processing the at least one electromyography signal using the calibration data to determine at least one biometric.