Generate Touch Input Signature for Discrete Cursor Movement

• US 20170220223A1
• Filed: 09/16/2014
• Published: 08/03/2017
• Est. Priority Date: 09/16/2014
• Status: Abandoned Application

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: KASRAVI, KAS, NIKOLSKY, OLEG VASSILIEVICH
• Application Number:
  US15/500,666
• Publication Number:
  US 20170220223A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 2200/1636 Sensing arrangement for detection of a tap gesture on the housing
• CPC Class Codes: G06F 3/0418 for error correction or compensation, e.g. based on parallax, calibration or alignment
• CPC Class Codes: G06F 3/04182 Filtering of noise external to the device and not generated by digitiser components
• CPC Class Codes: G06F 3/0488 using a touch-screen or digitiser, e.g. input of commands through traced gestures
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text

Abstract

Example techniques to generate a touch input signature for discrete cursor movement are disclosed. In one example implementation according to aspects of the present disclosure, a plurality of signals generated by a sensor of a computing system is analyzed. The plurality of signals correspond to a series of training touch inputs received on a surface of the computing system. A touch input signature for discrete cursor movement is then generated based on the plurality of signals corresponding to the series of training touch inputs.

Claims

1. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to:

analyze a plurality of signals generated by a sensor of a computing system, the plurality of signals corresponding to a series of training touch inputs received on a surface of the computing system; and

generate a touch input signature for discrete cursor movement based on the plurality of signals corresponding to the series of training touch inputs.

2. The non-transitory computer-readable storage medium of claim 1 storing instructions that, when executed by the processor, further cause the processor to:

determine whether the touch input signature is statistically significant; and

store the touch input signature to a data store responsive to determining that the touch input signature is statistically significant.

3. The non-transitory computer-readable storage medium of claim 1 storing instructions that, when executed by the processor, further cause the processor to:

de-noise the plurality of signals corresponding to the series of training touch inputs.

4. The non-transitory computer-readable storage medium of claim 3, wherein de-noising the plurality of signals further comprises applying a discrete wavelet transform to the plurality of signals.

5. The non-transitory computer-readable storage medium of claim 1, wherein touch input signature represent a tolerance band having an outer bound and inner bound.

6. The non-transitory computer-readable storage medium of claim 5 storing instructions that, when executed by the processor, further cause the processor to:

generate a discrete cursor movement from a set of discrete cursor movements when a detected touch input is substantially within the tolerance band.

7. A computing system comprising:

a sensor to generate a plurality of signals corresponding to a detected series of touch inputs on the computing system;

a touch input analysis module to analyze the plurality of signals generated by the sensor; and

a touch input signature generation module to generate a touch input signature for discrete cursor movement based on the analysis of the plurality of signals corresponding to the detected series of training touch inputs.

8. The computing system of claim 7, wherein the sensor comprises an accelerometer.

9. The computing system of claim 7, wherein the touch analysis module analyzes the plurality of signals generated by the sensor by:

de-noising the plurality of signals corresponding to the detected series of touch inputs; and

detecting any outlier in the plurality of signals corresponding to the detected series of touch inputs.

10. The computing system of claim 9, wherein de-noising the plurality of signals corresponding to the detected series of touch inputs includes applying a wavelet transform to the plurality of signals.

11. The computing system of claim 7, further comprising:

a statistical significance module to determine whether the touch input signature is statistically significant and to store the touch input signature to a data store responsive to determining that the touch input signature is statistically significant.

12. A method comprising:

generating, by a computing system, a plurality of signals corresponding to a series of training touch inputs received on a surface of the computing system;

generating, by the computing system, a touch input signature for discrete cursor movement based on the series of training touch inputs;

determining, by the computing system, whether the touch input signature is statistically significant; and

storing the touch input signature to a data store responsive to determining that the touch input signature is statistically significant.

13. The method of claim 12, further comprising:

de-noising, by the computing system, the plurality of signals corresponding to the series of training touch inputs.

14. The method of claim 12, wherein de-noising the plurality of signals further comprises applying a discrete wavelet transform to the plurality of signals.

15. The method of claim 12, wherein the touch input signature represents a tolerance band having an outer bound and an inner bound.