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http://dx.doi.org/10.5573/ieie.2015.52.3.089

Study on Compressed Sensing of ECG/EMG/EEG Signals for Low Power Wireless Biopotential Signal Monitoring  

Lee, Ukjun (Department of Wireless Communications Engineering, Kwangwoon University)
Shin, Hyunchol (Department of Wireless Communications Engineering, Kwangwoon University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.52, no.3, 2015 , pp. 89-95 More about this Journal
Abstract
Compresses sensing (CS) technique is beneficial for reducing power consumption of biopotential acquisition circuits in wireless healthcare system. This paper investigates the maximum possible compress ratio for various biopotential signal when the CS technique is applied. By using the CS technique, we perform the compression and reconstruction of typical electrocardiogram(ECG), electromyogram(EMG), electroencephalogram(EEG) signals. By comparing the original signal and reconstructed signal, we determines the validity of the CS-based signal compression. Raw-biopotential signal is compressed by using a psuedo-random matrix, and the compressed signal is reconstructed by using the Block Sparse Bayesian Learning(BSBL) algorithm. EMG signal, which is the most sparse biopotential signal, the maximum compress ratio is found to be 10, and the ECG'sl maximum compress ratio is found to be 5. EEG signal, which is the least sparse bioptential signal, the maximum compress ratio is found to be 4. The results of this work is useful and instrumental for the design of wireless biopotential signal monitoring circuits.
Keywords
무선헬스케어;생체신호;압축센싱;심전도;근전도;뇌전도;
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Times Cited By KSCI : 3  (Citation Analysis)
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