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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yih-Chun Cheng Pei-Yun Tsai |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Electr. Eng., Nat. Central Univ., Jhongli, Taiwan (Yih-Chun Cheng; Pei-Yun Tsai) |
| Abstract | In this paper, we present low-complexity compressed sensing (CS) techniques for monitoring electrocardiogram (ECG) signals in wireless body sensor network (WBSN). We first exploit ECG properties in the wavelet domain to extend the partially known support set (PKS) so as to reduce the support augmentation and estimation efforts in the iterative recovery algorithm. Then, variable orthogonal multi-matching pursuit (vOMMP) algorithm is proposed, which uses orthogonal matching pursuit (OMP) algorithm in the first phase to effectively augment the support set with reliable supports and adopts the orthogonal multi-matching pursuit (OMMP) in the second phase to rescue the missing supports. The reconstruction performance is thus enhanced. Furthermore, the computation-intensive pseudo-inverse operation for signal reconstruction is simplified by the matrix-inversion-free technique based on QR decomposition. The performance and complexity comparisons manifest the advantages of our proposed techniques. |
| Starting Page | 994 |
| Ending Page | 997 |
| File Size | 559006 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781479983919 |
| DOI | 10.1109/ISCAS.2015.7168803 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-24 |
| Publisher Place | Portugal |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Matching pursuit algorithms Complexity theory Electrocardiography Matrix decomposition Signal to noise ratio Compressed sensing Wireless sensor networks orthogonal multi-matching pursuit (OMMP) Compressed Sensing (CS) Electrocardiogram (ECG) digital wavelet transform (DWT) orthogonal matching pursuit (OMP) |
| Content Type | Text |
| Resource Type | Article |
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