Paper

Compressed Sensing System Considerations for ECG and EMG Wireless Bio-Sensors

Volume Number:
6
Issue Number:
2
Pages:
156
–
166
Publication Date:
April 2012

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Abstract

Compressed sensing (CS) is an emerging signal processing paradigm that enables sub-Nyquist processing of sparse signals such as electrocardiogram (ECG) and electromyogram (EMG) biosignals. Consequently, it can be applied to biosignal acquisition systems to reduce the data rate to realize ultra-low-power performance. CS is compared to conventional and adaptive sampling techniques and several system-level design considerations are presented for CS acquisition systems including sparsity and compression limits, thresholding techniques, encoder bit-precision requirements, and signal recovery algorithms. Simulation studies show that compression factors greater than 16X are achievable for ECG and EMG signals with signal-to-quantization noise ratios greater than 60 dB.

Description

A. M. R. Dixon, E. G. Allstot, D. Gangopadhyay and D. J. Allstot, "Compressed Sensing System Considerations for ECG and EMG Wireless Biosensors," in IEEE Transactions on Biomedical Circuits and Systems, vol. 6, no. 2, pp. 156-166, April 2012, doi: 10.1109/TBCAS.2012.2193668.