Method and system to detect two-hand gestures

Patent metadata

Field	Value
Publication number	US-12429956-B1
Application number	US-202418604361-A
Country	US
Kind code	B1
Filing date	Mar 13, 2024
Priority date	Mar 13, 2024
Publication date	Sep 30, 2025
Grant date	Sep 30, 2025

Abstract

A wearable device includes an accelerometer, at least three electrodes to detect electromyography signal, a communication circuitry, and a processor circuitry. A user wears a primary and a secondary wearable device on two limbs. When the user performs a two-hand gesture, the wearable devices detect a primary and a secondary movement pattern. The primary device recognizes the two-hand gesture from the primary and secondary movement pattern.

First claim

The invention claimed is:

1. A method to detect hand gestures, comprising:
receiving a first movement pattern by a first wearable device, the first wearable device, wherein receiving the first movement pattern by the first wearable device includes:
receiving a first plurality of acceleration data from a first accelerometer over a time period, the accelerometer being on the first wearable device; and
receiving a first plurality of electromyography (EMG) signals from a first EMG sensor on the first wearable device over the time period;

receiving a second movement pattern by a second wearable device, the second wearable device, wherein receiving the second movement pattern by the second wearable device includes:
receiving a second plurality of acceleration data from a second accelerometer on the second wearable device over the time period; and
receiving a second plurality of EMG signals from a second EMG sensor on the second wearable device over the time period;

transmitting the second movement pattern from the second wearable device to the first wearable device; and
detecting a gesture by the first wearable device, including:
matching a gesture from the gesture database with the first movement pattern and the second movement pattern, the matching including:
determining if the first movement pattern or the second movement pattern is invalid;
generating a fill movement pattern in response to determining at least one of the first movement pattern and the second movement pattern is invalid; and
replacing the one invalid movement pattern with the fill movement pattern.

2. The method of claim 1 , wherein transmitting the second movement pattern from the second wearable device to the first wearable device uses body contact transmission.

3. The method of claim 1 , further comprising:
generating a first analog signal from the first plurality of EMG signals, and
generating a second analog signal from the second plurality of EMG signals.

4. The method of claim 3 , wherein the first EMG sensor includes at least three electrodes, and the second EMG sensor includes at least three electrodes.

5. The method of claim 4 , further comprising:
processing the first analog signal to determine contraction or relaxation of a first hand, and
processing the second analog signal to determine contraction or relaxation of a second hand.

6. The method of claim 1 , wherein receiving a movement pattern further comprises:
validating the plurality of acceleration data from the accelerometer.

7. The method of claim 1 , wherein the matching algorithm is Dynamic Time Warping.

8. A system, comprising:
a first wearable device, configured to be worn by a user on a first limb, wherein the first wearable device includes:
a first accelerometer, the first accelerometer configured to detect acceleration in at least three axes;
at least three first electrodes, the first electrode configured to detect electromyography (EMG) signal;
a first processor circuitry,
a first memory, and
a first communication circuitry; and

a second wearable device, configured to be worn by the user on a second limb, the second wearable device being configured to:
detect a second limb movement of the second limb, and
transmit a second limb movement pattern to the first wearable device, the first wearable device begin configured to detect a gesture with the first processor circuitry in response to the second limb movement, wherein the first limb is a first arm of the user and the second limb is a second arm of the user, and the first wearable device is configured to generate a first analog signal from EMG signals detected by the at least three first electrodes over a time period with a first analog to digital converter, wherein the second limb movement pattern comprises:

a plurality of acceleration data over the time period, and
a second analog signal generated from EMG signals detected by at least three second electrodes over the time period, the first analog signal representing a first contraction or relaxation of a first hand of the user; and the second analog signal representing a second contraction or relaxation of a second hand of the user;
wherein the first wearable device is further configured to:

validate a first plurality of acceleration data detected by its accelerometer;
validate a second plurality of acceleration data included in the second limb movement pattern; and
if one of the first plurality of acceleration data or the second plurality of acceleration data is invalid:
generate a fill acceleration data; and
replace the one invalid plurality of acceleration data with the fill acceleration data.

9. The system of claim 8 , wherein the first communication circuitry includes body contact communication.

10. The system of claim 8 , wherein the first wearable device is configured to detect a gesture by performing:
executing, on the first processor circuitry, a matching algorithm to a gesture database, the gesture database being on the first memory; and
matching a gesture from the gesture database with the first plurality of acceleration data and the second plurality of acceleration data.

11. The system of claim 10 , wherein the matching algorithm is Dynamic Time Warping.

12. The system of claim 11 , wherein the first wearable device is configured to detect a gesture by further performing:
validating the matched gesture with the first analog signal and the second analog signal.

13. The system of claim 12 , wherein the first processor circuitry, the first communication circuitry, the first accelerometer, and the first analog digital converter are made on a single silicon die.

14. A system, comprising:
a first wearable device;
a second wearable device that includes:
an accelerometer;
at least three electrodes configured to detect electromyography signal;
a processing circuitry, and
a communication circuitry, the second wearable device configured to:
prepare a first movement pattern from a plurality of acceleration data from the accelerometer over a time period and a plurality of EMG signals from the at least three electrodes over the time period;
receive a second movement pattern from the first wearable device; and
match a gesture from a gesture database with the first movement pattern and the second movement pattern;
validate the first movement pattern;
validate the second movement pattern; and
if one of the first movement pattern or second movement pattern is invalid:
generate a fill movement pattern; and
replace the one invalid movement pattern with the fill movement pattern.

15. The system of claim 14 , wherein the communication circuitry includes body contact communication.

16. The system of claim 14 , wherein the first movement pattern further includes:
an analog signal generated from the at least three electrodes, the analog signal representing a contraction or relaxation of a hand of a user.

17. The wearable device of claim 16 , comprising:
an analog digital converter to generate the analog signal, wherein the processor circuitry, the communication circuitry, the accelerometer, and the analog digital converter are made on a single silicon die.

Assignees

• St Microelectronics Int Nv

Inventors

• Alessi Enrico Rosario
• Maio Alessandro
• Passaniti Fabio

Classifications

• A61B2562/0219

  Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches · CPC title

• A61B2562/028

  Microscale sensors, e.g. electromechanical sensors [MEMS] · CPC title

• G06F3/017 Primary

  Gesture based interaction, e.g. based on a set of recognized hand gestures (interaction based on gestures traced on a digitiser G06F3/04883) · CPC title

• G06F3/015 Primary

  Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection · CPC title

• G06V40/28

  Recognition of hand or arm movements, e.g. recognition of deaf sign language (static hand signs G06V40/113) · CPC title