TOUCH SENSOR GESTURE RECOGNITION FOR OPERATION OF MOBILE DEVICES

• US 20130257781A1
• Filed: 12/22/2010
• Published: 10/03/2013
• Est. Priority Date: 12/22/2010
• Status: Active Grant

• Current Assignee: Praem Phulwani, Rudy Yukich
• Original Assignee: Praem Phulwani, Rudy Yukich
• Inventors: Yukich, Rudy, Phulwani, Praem
• Granted Patent: US 9,524,041 B2
• Time in Patent Office: Days
• US Class Current: 345/173
• CPC Class Codes: G06F 3/041 Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
• CPC Class Codes: G06F 3/0416 Control or interface arrangements specially adapted for digitisers
• CPC Class Codes: G06F 3/042 by opto-electronic means
• CPC Class Codes: G06F 3/044 by capacitive means
• CPC Class Codes: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06F 3/04886 by partitioning the display area of the touch-screen or the surface of the digitising tablet into independently controllable areas, e.g. virtual keyboards or menus

Abstract

Touch sensor gesture recognition for operation of mobile devices. An embodiment of a mobile device may include a touch sensor for the detection of gestures, the touch sensor including sensor elements to generate touch sensor data for a detected gesture, and a processor to process the touch sensor data produced by the sensor elements of the touch sensor. In some embodiments the processor is to process the touch sensor data using a hybrid touch sensor algorithm, the hybrid touch sensor algorithm including a plurality of touch sensor algorithms, the plurality of touch sensor algorithms including a first algorithm and a second algorithm, where the processor dynamically changes between the plurality of algorithms depending on of the nature of the received touch sensor data. In some embodiments the processor utilizes a support vector machine with a radial basis function kernel in the interpretation of detected gestures. In some embodiments, the processor is to determine an alignment between a first input sequence of sensor data and a second input sequence of sensor data using dynamic time warping.

Claims

1. A mobile device comprising:

a touch sensor for the detection of gestures, the touch sensor including a plurality of sensor elements to generate touch sensor data for a detected gesture; and

a processor, the processor to process the touch sensor data produced by the sensor elements of the touch sensor;

wherein the processor is to process the touch sensor data using a hybrid touch sensor algorithm, the hybrid touch sensor algorithm including a plurality of touch sensor algorithms, the plurality of touch sensor algorithms including a first algorithm and a second algorithm, where the processor dynamically changes between the plurality of algorithms depending on the nature of the received touch sensor data.

2. The mobile device of claim 1, wherein the processor dynamically changing between the plurality of algorithms includes the processor switching from an active algorithm to another of the plurality of algorithms in response to the processor detecting rank skipping between the sensor elements in data produced by the active algorithm.

3. The mobile device of claim 2, wherein the first algorithm is a centroid algorithm, the centroid algorithm taking a weighted average of quantities derived from the plurality of sensor elements to determine a barycenter of a thumb or other finger performing the gesture.

4. The mobile device of claim 3, wherein the barycenter may be used for one of an absolute position of the thumb or other finger or differentiated to provide relative motion information.

5. The mobile device of claim 3, wherein the processor switching from an active algorithm to another of the plurality of algorithms in response to the processor detecting rank skipping comprises the hybrid algorithm switching to use of the centroid algorithm when the rank skipping is detected for another of the plurality of algorithms.

6. The mobile device of claim 2, wherein the second algorithm is a slider algorithm, the slider algorithm treating the sensor elements as being in ranks and operating to identify a position on one of the ranks.

7. The mobile device of claim 6, wherein determining the rank includes locating a distal-most rank meeting a certain threshold.

8. The mobile device of claim 6, wherein the slider algorithm is preferred when a tip of a thumb or other finger is located on an upper portion of the touch sensor.

9. A method comprising:

receiving touch sensor data for a mobile device, the touch sensor data representing a gesture input on the touch sensor;

processing the touch sensor data using a hybrid touch sensor algorithm, the hybrid touch sensor algorithm including a plurality of touch sensor algorithms including a first algorithm and a second algorithm; and

dynamically changing between algorithms of the plurality of algorithms depending on the received touch sensor data.

10. The method of claim 9, wherein dynamically changing between the plurality of algorithms includes switching to use another of the plurality of algorithms in response to detecting rank skipping between the sensor elements in data produced by the active algorithm.

11. The method of claim 10, wherein the first algorithm is a centroid algorithm, the centroid algorithm taking a weighted average of quantities derived from the plurality of sensor elements to determine a barycenter of a thumb or other finger performing the gesture.

12. The method of claim 11, wherein the barycenter may be used for one of an absolute position of the thumb or other finger or differentiated to provide relative motion information.

13. The method of claim 11, wherein switching from an active algorithm to another of the plurality of algorithms in response to detecting rank skipping comprises the hybrid algorithm switching to the centroid algorithm when the rank skipping is detected for another of the plurality of algorithms.

14. The method of claim 11, wherein the second algorithm is a slider algorithm, the slider algorithm treating the sensor elements as being in ranks and operating to identify a position on one of the ranks.

15. The method of claim 14, wherein determining the rank includes locating a distal-most rank meeting a certain threshold.

16. The method of claim 11, wherein the slider algorithm is preferred when a tip of a thumb or other finger is located on an upper portion of the touch sensor.

17-38. -38. (canceled)