DocumentCode :
178603
Title :
A low power self-capacitive touch sensing analog front end with sparse multi-touch detection
Author :
Chenchi Luo
Author_Institution :
Embedded Process. Syst. Lab., Texas Instrum., Dallas, TX, USA
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
3007
Lastpage :
3011
Abstract :
Capacitive sensing technology is ubiquitous in today´s electronic devices. This paper proposes a novel architecture for the design of an ultra low power self-capacitive touch sensing analog front end (AFE) by exploiting the sparsity of simultaneous touches with respect to the number of sensor nodes. It is possible to significantly reduce the complexity and the power consumption of the AFE by migrating the computational burden to the digital processor which usually have surplus computational power. Based on the 1-bit compressive sensing theory, the ADC(s) in the AFE can be replaced by a single comparator. The number of measurements required in order to resolve the touch positions is related to the number of simultaneous touches rather than the number of sensor nodes. Detailed AFE architecture and the capacitance measurement process will be presented along with a corresponding digital reconstruction algorithm run by the digital processor.
Keywords :
analogue-digital conversion; capacitance measurement; capacitive sensors; comparators (circuits); compressed sensing; digital signal processing chips; signal reconstruction; tactile sensors; ADC; AFE architecture; capacitance measurement process; comparator; complexity reduction; compressive sensing theory; digital processor; digital reconstruction algorithm; electronic device; power consumption reduction; self-capacitive touch sensing analog front end; sensor nodes; sparse multitouch detection; Capacitance; Charge transfer; Compressed sensing; Conductors; Electrodes; Reconstruction algorithms; Sensors; 1-bit compressive sensing; binary iterative hard thresholding; capacitive touch screen;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6854152
Filename :
6854152
Link To Document :
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