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Compressed Sensing System Considerations for ECG and EMG Wireless Biosensors

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4 Author(s)
Dixon, A.M.R. ; Dept. of Electr. Eng., Univ. of Washington, Seattle, WA, USA ; Allstot, E.G. ; Gangopadhyay, D. ; Allstot, D.J.

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.

Published in:

Biomedical Circuits and Systems, IEEE Transactions on  (Volume:6 ,  Issue: 2 )

Date of Publication:

April 2012

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