Detecting and using body tissue electrical signals

• US 10,070,799 B2
• Filed: 11/29/2017
• Issued: 09/11/2018
• Est. Priority Date: 12/02/2016
• Status: Active Grant

• Current Assignee: Pison Technology, Inc.
• Original Assignee: Pison Technology, Inc.
• Inventors: Ang, Dexter W., Cipoletta, David O, Karnes, Samuel J., Kowalczyk, Michael, Srikumar, Sidhant
• Primary Examiner(s): KIM, EUN HWA
• Application Number:
  US15/826,131
• Publication Number:
  US 20180153430A1
• Time in Patent Office: 286 Days
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 5/0024 for multiple sensor units attached to the patient, e.g. using a body or personal area network
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/053 Measuring electrical impedance or conductance of a portion of the body
• CPC Class Codes: A61B 5/1114 Tracking parts of the body
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/25 Bioelectric electrodes therefor
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/4851 Prosthesis assessment or monitoring
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6824 Arm or wrist
• CPC Class Codes: A61B 5/6829 Foot or ankle
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• 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 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: G06F 1/163 Wearable computers, e.g. on a belt
• CPC Class Codes: G06F 3/015 Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
• CPC Class Codes: G06F 3/0236 : using selection techniques to select from displayed items

Abstract

Bio-potentials are sensed on the skin of a subject. The bio-potentials include muscle bio-potentials, and nerve bio-potentials. Skin sensors are positioned to enable the sensing circuitry to emphasize the nerve bio-potentials and deemphasize the muscle bio-potentials in processed bio-potential signals generated by the sensing circuitry. A machine learning component identifies control sequences or tracks body motions based on the processed bio-potential signals.

Claims

1. A system, comprising:

a wireless wrist-mounted user interface device configured to enable a user to control a function of a target component by finger and hand motions, the wireless wrist-mounted user interface device comprising;

at least one pair of electrodes configured to be positioned adjacent to particular detection locations on the skin on top of a wrist of the user, each of the at least one pair of electrodes being configured to detect raw electrical potential that includes characteristics of electrical activity of (a) nerve tissue in the vicinity of the at least one pair of electrodes and (b) muscle tissue in the vicinity of the at least one pair of electrodes;

signal processing electronics comprising;

at least one filter configured to reduce amplitudes indicative of frequency components of the raw electrical potentials that are characteristic of the electrical activity of the muscle tissue in the vicinity of the at least one pair of electrodes and of noise so as to improve a signal-to-noise ratio of each of the raw electrical potentials;

a threshold processor configured to process each of the filtered raw electrical potentials and configured to provide an output signal only when an amplitude of each of the filtered raw electrical potentials exceeds a threshold, and

an analytical component configured to detect a differential signal between the output signals from the threshold processor and to use the differential signal to determine a direction of propagation of the electrical activity of the nerve tissue in the vicinity of the at least one pair of electrodes;

a data processor comprising;

storage containing historical information representative of known relationships between (a) features of data values generated from electrical potentials of nerve tissue previously detected by electrodes on wrists of users and (b) actions of particular muscles, gestures, or intent corresponding to the features of the stored data values,

a generator configured to generate data values based upon the differential signal representing the activity of the nerve tissue,

a feature extractor configured to extract features from the data generated by the generator, and

a component inferring actions of particular muscles, gestures or intent of the user based on (a) the stored historical information representative of the known relationships and (b) the extracted features from the data values; and

a controller configured to control the function of the target component based on the inferred actions of particular muscles, gestures, or intent.

2. The system of claim 1, comprising a structure to support the at least one pair of electrodes on the wrist.

3. The system of claim 2, comprising:

alignment features configured to align the structure relative to an upper surface and an outer edge of the wrist to position the at least one pair of electrodes in contact with the skin on top of the wrist and in a vicinity of particular internal tissues of the wrist.

4. The system of claim 3, in which the alignment features are configured to position the at least one pair of electrodes in contact with the top of the wrist.

5. The system of claim 1, wherein the at least one pair of electrodes comprising at least six electrodes.

6. The system of claim 1, in which each of the at least one pair of electrodes comprises a dry contact surface that is associated with a conductive solid gel, foam, or film.

7. The system of claim 1, comprising a resilient mounting for at least one of the pair of electrodes.

8. The system of claim 1, in which the component inferring actions comprises a classifier.

9. The system of claim 1, in which the component inferring actions infers actions based also on signals from an inertial measurement unit.

10. The system of claim 1, in which the component inferring actions infers actions based also on signals from an electrode external to the wireless wrist-mounted user interface device.

11. The system of claim 1, wherein the wireless wrist-mounted user interface device further comprises a user interface having one or more button controlled switches and a multi-color intensity controllable LED.

12. The system of claim 11, in which the user interface comprises haptic functions.

13. The system of claim 1, wherein the wireless wrist-mounted user interface device further comprises a port for connection of an electrical conductor between the port and an electrode configured to be adhered to another area of the skin of the user.

14. The system of claim 1, comprising another electrode configured to detect on another portion of the skin of the user, one or more electrical potentials characteristic of electrical activity of muscle tissue, the at least one filter configured to use the detected one or more electrical potentials characteristic from the other electrode for noise cancellation with respect to the detected raw electrical potentials.

15. The system of claim 1, comprising an impedance matching component configured to match the impedance of the at least one pair of electrodes to the impedance of the skin on top of the wrist.