Compressed Sensing System Considerations for ECG and EMG Wireless Biosensors

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-p...

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Veröffentlicht in:IEEE transactions on biomedical circuits and systems 2012-04, Vol.6 (2), p.156-166
Hauptverfasser: Dixon, A. M. R., Allstot, E. G., Gangopadhyay, D., Allstot, D. J.
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:1932-4545
1940-9990
DOI:10.1109/TBCAS.2012.2193668