TECHNIQUES FOR IMPROVED WEARABLE COMPUTING DEVICE GESTURE BASED INTERACTIONS

• US 20150301606A1
• Filed: 04/18/2014
• Published: 10/22/2015
• Est. Priority Date: 04/18/2014
• Status: Abandoned Application

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Andrei, Valentin
• Application Number:
  US14/256,076
• Publication Number:
  US 20150301606A1
• 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 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• 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

Abstract

Techniques for improved wearable computing device gesture based interactions are described. For example, an apparatus may comprise a band comprising one or more sensors arranged around a circumference of the band to monitor muscle activity and logic, at least a portion of which is in hardware, the logic to detect changes in muscle activity based on signals received from one or more of the one or more sensors and to interpret the detected changes in muscle activity as one or more gestures to control the apparatus. Other embodiments are described and claimed.

Claims

1. An apparatus, comprising:

a band comprising one or more sensors arranged around a circumference of the band to monitor muscle activity; and

logic, at least a portion of which is in hardware, the logic to detect changes in muscle activity based on signals received from one or more of the one or more sensors and to interpret the detected changes in muscle activity as one or more gestures to control the apparatus.

2. The apparatus of claim 1, the apparatus comprising a wearable computing device and the band to substantially encircle a portion of a human arm, wrist or hand.

3. The apparatus of claim 1, the one or more sensors comprising pressure sensors to monitor contraction and extension of one or more muscles in one or more of a human arm, wrist or hand.

4. The apparatus of claim 1, the band comprising an elastic material or an adjustable closure to ensure contact between the one or more sensors and a human arm, wrist or hand.

5. The apparatus of claim 1, the one or more gestures comprising a recognizable muscle contraction pattern detected based on movement of one or more of a human arm, wrist, hand or one or more digits of the hand.

6. The apparatus of claim 5, the movement of one or more of the human arm, wrist, hand or one or more digits of the hand allowing for continuous viewing of a display of the apparatus during the movement.

7. The apparatus of claim 1, the logic to:

detect a gesture;

compare the detected gesture to one or more gesture templates; and

control the apparatus based on an action associated with the detected gesture if the detected gesture matches one of the one or more gesture templates.

8. The apparatus of claim 1, the logic to:

initiate a training mode based on a signal received from one or more input devices of the apparatus, the one or more input devices comprising a mechanical input device, touch input device, or gesture input device; and

detect multiple executions of a new gesture.

9. The apparatus of claim 8, the logic to:

compare features detected based on each of the multiple executions of the new gesture;

determine a variability of the new gesture based on the comparison;

save the new gesture if the variability is less than or equal to a variability threshold; and

disregard the new gesture if the variability is greater than the variability threshold.

10. The apparatus of claim 8, the logic to:

compare features of the new gesture to one or more gesture templates;

determine a similarity of the new gesture and the one or more gesture templates;

save the new gesture if the similarity is less than or equal to a similarity threshold; and

disregard the new gesture if the similarity is greater than the similarity threshold.

11. The apparatus of claim 1, the one or more sensors communicatively coupled together using one or more flexible circuits.

12. A computer-implemented method, comprising:

detecting changes in muscle activity based on signals received from one or more of one or more sensors of a band comprising one or more sensors arranged around a circumference of the band; and

interpreting the detected changes in muscle activity as one or more gestures to control a wearable computing device comprising the band.

13. The computer-implemented method of claim 12, comprising:

detecting a gesture;

comparing the detected gesture to one or more gesture templates; and

controlling the wearable computing device based on an action associated with the detected gesture if the detected gesture matches one of the one or more gesture templates.

14. The computer-implemented method of claim 12, comprising:

receiving a signal from one or more input devices of the wearable computing device, the one or more input devices comprising a mechanical input device, touch input device, or gesture input device;

initiating a training mode based on the received signal; and

detecting multiple executions of a new gesture.

15. The computer-implemented method of claim 14, comprising:

generating a graphical user interface (GUI) element for display on a display of the wearable computing device, the GUI element comprising instructions for executing a new gesture in the training mode.

16. The computer-implemented method of claim 14, comprising:

comparing features detected based on each of the multiple executions of the new gesture; and

determining a variability of the new gesture based on the comparison.

17. The computer-implemented method of claim 16, comprising:

saving the new gesture if the variability is less than or equal to a variability threshold;

or

disregarding the new gesture if the variability is greater than the variability threshold.

18. The computer-implemented method of claim 14, comprising:

comparing features of the new gesture to one or more gesture templates; and

determining a similarity of the new gesture and the one or more gesture templates.

19. The computer-implemented method of claim 18, comprising:

saving the new gesture if the similarity is less than or equal to a similarity threshold;

or

disregarding the new gesture if the similarity is greater than the similarity threshold.

20. An article comprising a non-transitory storage medium containing a plurality of instructions that if executed enable a system to:

detect changes in muscle activity based on signals received from one or more of one or more sensors of a band comprising one or more sensors arranged around a circumference of the band; and

interpret the detected changes in muscle activity as one or more gestures to control a wearable computing device comprising the band.

21. The article of claim 20, comprising instructions that if executed enable the system to:

detect a gesture;

compare the detected gesture to one or more gesture templates; and

control the wearable computing device based on an action associated with the detected gesture if the detected gesture matches one of the one or more gesture templates.

22. The article of claim 20, comprising instructions that if executed enable the system to:

receive a signal from one or more input devices of the wearable computing device, the one or more input devices comprising a mechanical input device, touch input device, or gesture input device;

initiate a training mode based on the received signal; and

detect multiple executions of a new gesture.

23. The article of claim 22, comprising instructions that if executed enable the system to:

generate a graphical user interface (GUI) element for display on a display of the wearable computing device, the GUI element comprising instructions for executing a new gesture in the training mode.

24. The article of claim 22, comprising instructions that if executed enable the system to:

compare features detected based on each of the multiple executions of the new gesture;

determine one or more a variability of the new gesture based on the comparison;

compare features of the new gesture to one or more gesture templates; and

determine a similarity of the new gesture and the one or more gesture templates.

25. The article of claim 24, comprising instructions that if executed enable the system to:

save the new gesture if the variability is less than or equal to a variability threshold;

disregard the new gesture if the variability is greater than the variability threshold;

save the new gesture if the similarity is less than or equal to a similarity threshold;

or

disregard the new gesture if the similarity is greater than the similarity threshold.