Paper
12 March 2015 Efficient capacitive touch sensing using structured matrices
Author Affiliations +
Proceedings Volume 9401, Computational Imaging XIII; 94010O (2015) https://doi.org/10.1117/12.2075635
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
Compressive sensing is a technique used in signal processing applications to reduce sampling time. This paper talks about an efficient sampling framework based on compressive sensing for capacitive touch technology. We aim to minimize the number of measurements required during capacitance touch sensing process and in order to achieve this, we use structured matrices which can be used as a driving sensing framework for a touch controller. The novel contribution of this research is that we have modelled our recovery algorithm according to the structure of our sampling matrix, thus making it extremely efficient and simple to implement in a practical application. In this paper, we exploit the structure of the sensing matrix and conduct experiments to test the robustness of our proposed algorithm. Calculations of the floating point multiplication operations for the reconstruction algorithm and sensing matrix have also been looked into detail.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Humza Akhtar and Ramakrishna Kakarala "Efficient capacitive touch sensing using structured matrices", Proc. SPIE 9401, Computational Imaging XIII, 94010O (12 March 2015); https://doi.org/10.1117/12.2075635
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KEYWORDS
Signal to noise ratio

Reconstruction algorithms

Matrices

Compressed sensing

Electrodes

Capacitance

Structural sensing

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