Signal processing systems

• US 10,282,038 B2
• Filed: 10/04/2016
• Issued: 05/07/2019
• Est. Priority Date: 08/27/2010
• Status: Active Grant

• Current Assignee: InputDynamics Limited
• Original Assignee: InputDynamics Limited
• Inventors: Godsill, Simon, Bisutti, Giovanni, Christensen, Jens
• Primary Examiner(s): Flores, Roberto W
• Application Number:
  US15/284,740
• Publication Number:
  US 20170024032A1
• Time in Patent Office: 945 Days
• Field of Search: 345173, 345177, 345178, 178 1804
• CPC Class Codes: G06F 3/043 using propagating acoustic waves
• CPC Class Codes: G06F 3/0433 in which the acoustic waves are either generated by a movable member and propagated within a surface layer or propagated within a surface layer and captured by a movable member

Abstract

This invention relates to methods, apparatus, and computer program code for processing acoustic signal data to determine where an object has been tapped with a stylus, finger nail or the like. The method involved storing a set of labelled training data comprising digitized waveforms from a sensor for taps at a plurality of different locations. The labelled training data is then processed to determine mean value and covariance data for the waveforms, which is afterwards used in conjunction with a digitized waveform of a tap at an unknown location to identify the location of the tap. Preferably the covariance is decomposed into a plurality of basis functions for each region each with a respective weighting, which are used to represent captured data for an unknown tap and parameters of the representation are classified to locate the tap.

Claims

1. A user interface system for a mobile phone, wherein the system is configured to detect the location of a tap on the mobile phone having at least one acoustic sensor, wherein the system is configured to perform operations comprising:

storing a set of labelled training data, said set of labelled training data comprising digitised waveform data of waveforms captured from said acoustic sensor for taps at a plurality of different locations on said mobile phone in combination with location data indicating for each said waveform the location of the tap;

processing said set of labelled training data to determine, for each of a plurality of tap-sensing regions of said mobile phone, mean value data and covariance data for at least two said waveforms captured from taps in the said region, said mean value data defining a mean of said at least two waveforms and said covariance data defining covariance of said at least two waveforms;

capturing tap data comprising a digitised waveform of a tap at an unknown location captured by said acoustic sensor;

determining a tapped region of said mobile phone from said tap data and from said mean value data and said covariance data from said plurality of tap-sensing regions; and

outputting data representing detection of a user tap on the tapped region for controlling a function of the mobile phone;

wherein said processing of said set of labelled training data further comprises decomposing said covariance of said at least two waveforms into a plurality of basis functions each with a respective weighting, wherein said covariance data comprises data defining said respective weightings and providing basis function data defining said basis functions; and

wherein said determining of said tapped region comprises determining said tapped region from said tap data and from said mean value data and covariance data from said plurality of tap-sensing regions and from said basis function data.

2. A user interface system as claimed in claim 1 wherein said determining of said tapped region comprises determining from said captured tap data and from said mean value data and said covariance data from said plurality of tap-sensing regions, probability data defining a probability, for each of said tap-sensing regions, that said unknown location is in said region;

and

determining a said tapped region of said mobile phone for said unknown location from said probability data.

3. A user interface system as claimed in claim 2 wherein said determining of said probability data comprises determining, for each said region and for each of a plurality of possible tap times, a probability of capturing said captured tap data.

4. A user interface system as claimed in claim 3 wherein the system is further configured to perform operations comprising pre-processing said captured tap data to identify a subset of said possible tap times for said determining of said probability data.

5. A user interface system as claimed in claim 3 wherein said determining of said tapped region further comprises scaling said probability for each of said regions by one or both of:

i) a probability of no tap having been captured; and

ii) a prior probability of a said tap in the region for each of said plurality of possible tap times.

6. A user interface system as claimed in claim 1 wherein a different set of said functions is determined for each said region.

7. A user interface system as claimed in claim 1 further comprising determining at least one said basis function common to said plurality of tap-sensing regions.

8. A user interface system as claimed in claim 1 wherein said determining of said tapped region comprises, for each said region, estimating a set parameters to represent said captured data in terms of said basis functions for said region, and determining said tapped region by classifying said estimated sets of parameters for said regions.

9. A user interface system as claimed in claim 1 wherein said determining of said tapped region comprises operating on said captured tap data with a filter using each of said basis functions.

10. A user interface system as claimed in claim 1 wherein said determining of said probability data comprises determining, for each said region and for each of a plurality of possible tap times, a probability of capturing said captured tap data, and wherein said determining of said tapped region comprises determining, for each said region, j, and for a set of possible tap times n0, and for captured tap data y, a said probability p(y|j,n₀), or a log likelihood ratio dependent on said probability p(y|j,n₀), by applying to said data y a first FIR filter having coefficients determined by values of t, where t represents a said set of basis functions for region j, and a second FIR filter having coefficients determined by values of said mean value data.

11. A user interface system as claimed in claim 1 wherein the system is further configured to perform operations comprising determining a posterior tap probability

p(j,n₀|y)∝

p(y|j,n₀)p(j,n₀)

for a set of time offsets n₀ and tap positions j and determining an estimated tap position j at estimated time offset n⁰ from;

ĵ

,{circumflex over (n)}₀=argmax_j,n0p(j,n₀|y).

12. A user interface system as claimed in claim 1 wherein the system is further configured to perform operations comprising modelling at least part of said digitised waveform of a tap as