Sequential energy detection for touch input detection

In this paper we propose a novel detection algorithm that delivers impressive savings in the sensing time of the capacitive touchscreen systems using sequential energy detection methods. We also show that these savings can translate into a significant boost to the operational battery life of today's mobile devices. We provide numerical analysis of sequential energy detection scheme, and the average sample number of measurements required to decide the presence of a touch input is derived. The analysis and simulation results confirm that the proposed scheme can save at least 70% or more computational resources for performing touch detection under realistic noise condition as compared to the conventional fixed sample size detection scheme.

[1]  S. Frick,et al.  Compressed Sensing , 2014, Computer Vision, A Reference Guide.

[2]  Nan Sun,et al.  Multi-Channel Sparse Data Conversion With a Single Analog-to-Digital Converter , 2012, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[3]  Richard G. Baraniuk,et al.  The compressive multiplexer for multi-channel compressive sensing , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[4]  J. Andel.  Sequential Analysis , 2022, The SAGE Encyclopedia of Research Design.

[5]  Gernot Heiser,et al.  An Analysis of Power Consumption in a Smartphone , 2010, USENIX Annual Technical Conference.

[6]  Harry L. Van Trees,et al.  Detection, Estimation, and Modulation Theory, Part I , 1968 .

[7]  James H. McClellan,et al.  Compressive Sensing for Sparse Touch Detection on Capacitive Touch Screens , 2012, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[8]  Jungwoo Lee,et al.  A programmable mutual capacitance sensing circuit for a large-sized touch panel , 2012, 2012 IEEE International Symposium on Circuits and Systems.

[9]  Hyungcheol Shin,et al.  Low noise capacitive sensor for multi-touch mobile handset's applications , 2010, 2010 IEEE Asian Solid-State Circuits Conference.

[10]  C.E. Shannon,et al.  Communication in the Presence of Noise , 1949, Proceedings of the IRE.

[11]  H. V. Trees.  Detection, Estimation, And Modulation Theory , 2001 .

[12]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[13]  Bernard C. Levy,et al.  Principles of Signal Detection and Parameter Estimation , 2008 .