Method for determining a touch event and touch sensitive device

• US 8,619,063 B2
• Filed: 07/08/2011
• Issued: 12/31/2013
• Est. Priority Date: 07/09/2010
• Status: Active Grant

• Current Assignee: Elo Touch Solutions, Inc.
• Original Assignee: Elo Touch Solutions, Inc.
• Inventors: Chaine, Sebastien, Farah, Georges
• Primary Examiner(s): CERULLO, LILIANA P
• Application Number:
  US13/808,058
• Publication Number:
  US 20130257821A1
• Time in Patent Office: 907 Days
• Field of Search: 345173-178, 178/18.01, 17820101- 2004, 367118-129, 341/5, 327551-558, 3404071-4072
• US Class Current: 345/177
• 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
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text

Abstract

The invention relates to a method for determining a touch event provided by a user on an interaction surface of a touch sensitive device comprising the steps of: sensing a raw signal by a transducer, in particular by a piezoelectric transducer and low-pass filtering the sensed signal, segmenting the filtered raw signal into a baseline signal and at least one useful signal, and analyzing the at least one useful signal to determine properties of the touch event.

Claims

1. Method for determining a touch event provided by a user on an interaction surface of a touch sensitive device comprising the steps of:

a. sensing a raw signal by a piezoelectric transducer and low-pass filtering the sensed signal,

b. segmenting the filtered raw signal into a baseline signal and at least one useful signal by applying an expectation maximization algorithm (EM) to the filtered raw signal, wherein the baseline signal corresponds to noise and the at least one useful signal corresponds to a touch event, and

c. analyzing the at least one useful signal to determine properties of the touch event.

2. Method according to claim 1, wherein step b) comprises applying a statistical model to segment the filtered raw signal.

3. Method according to claim 1, wherein step b) is carried out in the time domain.

4. Method according to claim 1, wherein the filter has a maximal passing frequency of 100 Hz, in particular 50 Hz, more in particular 30 Hz.

5. Method according to claim 1, wherein step b) further comprises a classification expectation maximization algorithm (CEM).

6. Method according to claim 2, wherein to apply the statistical model, it is assumed that both baseline and useful signals each have a Gaussian distribution and their signal energies follow Gamma distributions.

7. Method according to claim 6, wherein at an initialization step of the expectation maximization algorithm, the variances of the Gaussian distribution of the baseline signal and the Gaussian distribution of the useful signal are based on signal energy, wherein the useful signal class relates to maximal energy, and wherein the baseline class relates to the median energy.

8. Method according to claim 1, wherein during segmenting in step b) a stream of a predetermined duration of the sensed signal is analyzed.

9. Method according to claim 8, wherein subsequent streams overlap.

10. Method according to claim 9, wherein when during step b) the same useful signal has been identified in a predetermined amount of streams, and the following stream does not overlap with the part up to the end of the useful signal of the precedent stream.

11. Method according to claim 8, wherein the stream has a length of at most two seconds.

12. Method according to claim 1, wherein step c) comprises attributing a touch event as soon a useful signal has been transmitted to step c.

13. Method according to claim 1, wherein step a) comprises sensing raw signals by more than one transducer and carrying out step b) for each one of the sensed signals.

14. Method according to claim 13, wherein step c) comprises identifying at least one of various types of gestures, the various types of gestures including one or more of drag, direction of drag, rotate, direction of rotation, zoom-in, and zoom-out, based on at least one of the time delay between one or more predetermined characteristics of the useful touch signals identified during step b) and their relative values for the more than one sensed raw signals.

15. Method according to claim 14, wherein the one or more predetermined characteristics relate to the position of the maximal, minimal or signal average crossing of the useful signal.

16. Method according to claim 14, wherein the type of gesture is only determined based on the time delay and the positions of the transducer with respect to the interaction surface.

17. Method according to claim 1, further comprising a step of smoothing the useful signal prior to step c).

18. Non-transitory computer program product comprising one or more computer readable media having computer executable instructions for performing the method of claim 1.

19. Touch sensitive device comprising an interaction surface for receiving touch events provided by a user and at least one piezoelectric transducer for sensing a signal, a low-pass filter unit, and a signal analyzing unit configured to identify the touch event according to the method to of claim 1.

20. Mobile device comprising a touch sensitive device according to claim 19.

21. Mobile device according to claim 20, wherein at least one of a front or and a backside of the mobile device comprises a touch sensitive device comprising an interaction surface for receiving touch events provided by a user and at least one piezoelectric transducer for sensing a signal, a low-pass filter unit and, a signal analyzing unit configured to identify the touch event, and wherein a display device is provided on the front side.