Matrix-Inversion-Free Compressed Sensing with Variable Orthogonal Multi-Matching Pursuit Based on Prior Information for ECG Signals

Yih Chun Cheng, Pei Yun Tsai, Ming Hao Huang

研究成果: 雜誌貢獻期刊論文同行評審

25 引文 斯高帕斯(Scopus)

摘要

Low-complexity compressed sensing (CS) techniques for monitoring electrocardiogram (ECG) signals in wireless body sensor network (WBSN) are presented. The prior probability of ECG sparsity in the wavelet domain is first exploited. Then, variable orthogonal multi-matching pursuit (vOMMP) algorithm that consists of two phases is proposed. In the first phase, orthogonal matching pursuit (OMP) algorithm is adopted to effectively augment the support set with reliable indices and in the second phase, the orthogonal multi-matching pursuit (OMMP) is employed to rescue the missing indices. The reconstruction performance is thus enhanced with the prior information and the vOMMP algorithm. Furthermore, the computation-intensive pseudo-inverse operation is simplified by the matrix-inversion-free (MIF) technique based on QR decomposition. The vOMMP-MIF CS decoder is then implemented in 90 nm CMOS technology. The QR decomposition is accomplished by two systolic arrays working in parallel. The implementation supports three settings for obtaining 40, 44, and 48 coefficients in the sparse vector. From the measurement result, the power consumption is 11.7 mW at 0.9 V and 12 MHz. Compared to prior chip implementations, our design shows good hardware efficiency and is suitable for low-energy applications.

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文章編號7473850
頁(從 - 到)864-873
頁數10
期刊IEEE Transactions on Biomedical Circuits and Systems
10
發行號4
DOIs
出版狀態已出版 - 8月 2016

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