Method and apparatus for differentiating touch screen users based on touch event analysis

• US 10,599,251 B2
• Filed: 03/21/2016
• Issued: 03/24/2020
• Est. Priority Date: 09/11/2014
• Status: Active Grant

• Current Assignee: Qeexo Co. (TDK Corporation)
• Original Assignee: Qeexo Co. (TDK Corporation)
• Inventors: Schwarz, Julia, Harrison, Chris
• Primary Examiner(s): Johnson, Gerald
• Application Number:
  US15/075,648
• Publication Number:
  US 20170024055A1
• Time in Patent Office: 1,464 Days
• CPC Class Codes: G06F 2203/04105 Pressure sensors for measuring the pressure or force exerted on the touch surface without providing the touch position
• 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 3/043 using propagating acoustic waves

Abstract

Some embodiments of the present invention include a method of differentiating touch screen users based on characterization of features derived from the touch event acoustics and mechanical impact and includes detecting a touch event on a touch sensitive surface, generating a vibro-acoustic waveform signal using at least one sensor detecting such touch event, converting the waveform signal into at least a domain signal, extracting distinguishing features from said domain signal, and classifying said features to associate the features of the domain signal with a particular user.

Claims

1. An apparatus for differentiating touch screen users based on characterization of features derived from touch event acoustics and mechanical impact, the apparatus comprising:

a touch sensitive surface for detecting a touch event from at least one user;

at least one sensor for generating a waveform signal in response to the touch event;

a converter for converting the waveform signal into at least a domain signal;

a feature extractor for extracting distinguishing features from the domain signal; and

a classification unit for employing the distinguishing features of the feature extractor to associate the distinguishing features of the domain signal with touch feature properties for a particular user.

2. The apparatus recited in claim 1, wherein the at least one sensor comprises a senor for detecting an acoustic effect of the touch event.

3. The apparatus recited in claim 1, wherein the at least one sensor comprises a senor for detecting a mechanical impact effect of the touch event.

4. The apparatus recited in claim 1, wherein the domain signal is a time domain signal.

5. The apparatus recited in claim 1, wherein the domain signal is a frequency domain signal.

6. The apparatus recited in claim 1, wherein the distinguishing features depend at least in part on physical characteristics of a finger used to create the touch event.

7. The apparatus recited in claim 1, wherein the distinguishing features depend at least in part on the magnitude of an impact used to create the touch event.

8. The apparatus recited in claim 1, wherein the at least one sensor comprises a sensor for detecting vibrations initiated by the touch event.

9. The apparatus recited in claim 1, wherein the at least one sensor comprises a sensor taken from a group of sensors consisting of impact sensors, vibration sensors, accelerometers, strain gauges, piezo-electric devices and acoustic sensors.

10. The apparatus recited in claim 1, wherein the distinguishing features are extracted based on at least one computation of a characteristic taken from a group consisting of average, standard deviation, variance, skewness, kurtosis, sum, root mean square, crest factor, dispersion, entropy, power sum, center of mass, coefficient of variation, cross-correlation, zero-crossings, seasonality, direct current bias, spectral centroid, spectral density, spherical harmonics, spectral energy, band energy ratio, by spectral band ratios, cepstral coefficients and fast Fourier transform content.

11. A computer-implemented method for differentiating touch screen users based on characterization of features derived from touch event acoustics and mechanical impact, the computer-implemented method comprising the following steps:

detecting a touch event on a touch sensitive surface;

generating a waveform signal using at least one sensor detecting the touch event;

converting the waveform signal into at least a domain signal;

extracting distinguishing features from the domain signal; and

employing the distinguishing features to associate the distinguishing features of the domain signal with touch feature properties for a particular user.

12. The computer-implemented method recited in claim 11, wherein the generating comprises using the at least one sensor for detecting an acoustic effect of a touch event.

13. The computer-implemented method recited in claim 11, wherein the generating comprises using the at least one sensor for detecting a mechanical impact effect of the touch event.

14. The computer-implemented method recited in claim 11, wherein the converting comprises converting the waveform signal into a time domain signal.

15. The computer-implemented method recited in claim 11, wherein the converting comprises converting the waveform signal into a frequency domain signal.

16. The computer-implemented method recited in claim 11, wherein the extracting comprises determining at least a portion of the distinguishing features based at least in part on physical characteristics of a finger used to create the touch event.

17. The computer-implemented method recited in claim 11, wherein the extracting comprises determining at least a portion of the distinguishing features based at least in part on magnitude of an impact used to create the touch event.

18. The computer-implemented method recited in claim 11, wherein the generating comprises using the at least one sensor to detect vibrations initiated by the touch event.

19. The computer-implemented method recited in claim 11, wherein the at least one sensor comprises a sensor taken from a group of sensors consisting of impact sensors, vibration sensors, accelerometers, strain gauges, piezo-electric devices and acoustic sensors.

20. The computer-implemented method recited in claim 11, wherein the distinguishing features are extracted based on at least one computation of a characteristic taken from a group consisting of average, standard, deviation, variance, skewness, kurtosis, sum, root mean square, crest factor, dispersion, entropy, power sum, center of mass, coefficient variation, cross-correlation, zero-crossings, seasonality, direct current bias, spectral centroid, spectral density, spherical harmonics, spectral energy, band energy ratio, log spectral band ratios, cepstral coefficients and fast Fourier transform content.

21. A non-transitory computer readable medium containing program instructions for using detected touch screen events to associate particular users with the detected touch screen events, wherein execution of the program instructions by a processor causes the processor to carry out the steps of:

generating a waveform signal using at least one sensor detecting a touch event;

converting the waveform signal into at least a domain signal;

extracting distinguishing features from the domain signal; and

employing the distinguishing features to associate the distinguishing features of the domain signal with touch feature properties for a particular user.

22. The non-transitory computer readable medium of claim 21, wherein the generating comprises using the at least one sensor for detecting an acoustic effect of the touch event.

23. The non-transitory computer readable medium of claim 21, wherein the generating comprises using the at least one sensor for detecting a mechanical impact effect of the touch event.

24. The non-transitory computer readable medium of claim 21, wherein the converting comprises converting the waveform signal into a time domain signal.

25. The non-transitory computer readable medium of claim 21, wherein the converting comprises converting the waveform signal into a frequency domain signal.

26. The non-transitory computer readable medium of claim 21, wherein the extracting comprises determining at least a portion of the distinguishing features based at least in part on physical characteristics of a finger used to create the touch event.

27. The non-transitory computer readable medium of claim 21, wherein the extracting comprises determining at least a portion of the distinguishing features based at least in part on magnitude of an impact used to create the touch event.

28. The non-transitory computer readable medium of claim 21, wherein the generating comprises using the at least one sensor to detect vibrations initiated by the touch event.

29. The non-transitory computer readable medium of claim 21, wherein the at least one sensor comprises a sensor taken from a group of sensors consisting of impact sensors, vibration sensors, accelerometers, strain gauges, piezo-electric devices and acoustic sensors.