CONTROLLING A WEARABLE DEVICE USING GESTURES

• US 20160282947A1
• Filed: 03/26/2015
• Published: 09/29/2016
• Est. Priority Date: 03/26/2015
• Status: Abandoned Application

• Current Assignee: Lenovo Singapore Pte Limited (Lenovo Group Ltd.)
• Original Assignee: Lenovo Singapore Pte Limited (Lenovo Group Ltd.)
• Inventors: Schwarz, David Alexander, Qian, Ming, Bula, Geoffrey Simon, Nicholson, John Weldon
• Application Number:
  US14/669,387
• Publication Number:
  US 20160282947A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 1/163 Wearable computers, e.g. on a belt
• CPC Class Codes: G06F 2200/1637 Sensing arrangement for detection of housing movement or orientation, e.g. for controlling scrolling or cursor movement on the display of an handheld computer
• CPC Class Codes: G06F 2203/0381 Multimodal input, i.e. interface arrangements enabling the user to issue commands by simultaneous use of input devices of different nature, e.g. voice plus gesture on digitizer
• CPC Class Codes: G06F 3/014 Hand-worn input/output arrangements, e.g. data gloves
• 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 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06F 3/0338 with detection of limited linear or angular displacement of an operating part of the device from a neutral position, e.g. isotonic or isometric joysticks
• CPC Class Codes: G06F 3/0346 with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06V 40/28 Recognition of hand or arm movements, e.g. recognition of deaf sign language static hand signs G06V40/113

Abstract

One embodiment provides a method including: receiving, at a wearable device, non-image data from at least one sensor operatively coupled to the wearable device, wherein the non-image data is based upon a gesture performed by a user; identifying, using a processor, the gesture performed by a user using the non-image data; and performing an action based upon the gesture identified. Other aspects are described and claimed.

Claims

1. A method, comprising:

receiving, at a wearable device, non-image data from at least one sensor operatively coupled to the wearable device, wherein the non-image data is based upon a gesture performed by a user;

identifying, using a processor, the gesture performed by a user using the non-image data; and

performing an action based upon the gesture identified.

2. The method of claim 1, wherein the non-image data comprises at least one of:

electromyography data, pressure data, and inertial data.

3. The method of claim 1, wherein the identifying comprises associating the non-image data with a gesture.

4. The method of claim 1, wherein the non-image data comprises an electromyography data stream, a pressure sensor data stream, and an inertial data stream, and wherein the identifying comprises using each of the data streams to extract at least one feature of the gesture.

5. The method of claim 4, further comprising aggregating the data streams into a single nonlinear model.

6. The method of claim 5, wherein the aggregating comprises using an unscented Kalman filter.

7. The method of claim 1, wherein the non-image data comprises an electromyography data stream, a pressure sensor data stream, and an inertial data stream and wherein the identifying comprises combining the data streams.

8. The method of claim 7, wherein the identifying comprises classifying the combined data streams using at least one support vector machine.

9. The method of claim 1, wherein the performing an action comprises controlling an alternate device using the gesture identified.

10. The method of claim 1, further comprising associating the gesture with an action.

11. A wearable device, comprising:

a wearable housing;

a display screen;

at least one sensor;

a processor operatively coupled to the display screen and the at least one sensor and housed by the wearable housing; and

a memory that stores instructions executable by the processor to;

receive non-image data from the at least one sensor, wherein the non-image data is based upon a gesture performed by a user;

identify the gesture performed by a user using the non-image data; and

perform an action based upon the gesture identified.

12. The wearable device of claim 11, wherein the non-image data comprises at least one of:

electromyography data, pressure data, and inertial data.

13. The wearable device of claim 11, wherein to identify comprises associating the non-image data with a gesture.

14. The wearable device of claim 11, wherein the non-image data comprises an electromyography data stream, a pressure sensor data stream, and an inertial data stream, and wherein to identify comprises using each of the data streams to extract at least one feature of the gesture.

15. The wearable device of claim 14, wherein the instructions are further executable by the processor to aggregate the data streams into a single nonlinear model.

16. The wearable device of claim 15, wherein to aggregate comprises using an unscented Kalman filter.

17. The wearable device of claim 11, wherein the non-image data comprises an electromyography data stream, a pressure sensor data stream, and an inertial data stream and wherein to identify comprises combining the data streams.

18. The wearable device of claim 17, wherein to identify comprises classifying the combined data streams using at least one support vector machine.

19. The wearable device of claim 11, wherein to perform an action comprises controlling an alternate device using the gesture identified.

20. A product, comprising:

a storage device that stores code executable by a processor, the code comprising;

code that receives, at a wearable device, non-image data from at least one sensor operatively coupled to the wearable device, wherein the non-image data is based upon a gesture performed by a user;

code that identifies the gesture performed by a user using the non-image data; and

code that performs an action based upon the gesture identified.