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Content Provider | IEEE Xplore Digital Library |
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Author | Avonds, Y. Yipeng Liu Van Huffel, S. |
Copyright Year | 2014 |
Description | Author affiliation: Dept. of Electr. Eng., KU Leuven, Leuven, Belgium (Avonds, Y.; Yipeng Liu; Van Huffel, S.) |
Abstract | This paper addresses compressive sensing for multi-channel ECG. Compared to the traditional sparse signal recovery approach which decomposes the signal into the product of a dictionary and a sparse vector, the recently developed cosparse approach exploits sparsity of the product of an analysis matrix and the original signal. We apply the cosparse Greedy Analysis Pursuit (GAP) algorithm for compressive sensing of ECG signals. Moreover, to reduce processing time, classical signal-channel GAP is generalized to the multi-channel GAP algorithm, which simultaneously reconstructs multiple signals with similar support. Numerical experiments show that the proposed method outperforms the classical sparse multi-channel greedy algorithms in terms of accuracy and the single-channel cosparse approach in terms of processing speed. |
Sponsorship | IEEE Eng. Med. Biol. Soc. |
Starting Page | 6385 |
Ending Page | 6388 |
File Size | 616804 |
Page Count | 4 |
File Format | |
ISBN | 9781424479290 |
ISSN | 1557170X |
DOI | 10.1109/EMBC.2014.6945089 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-08-26 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Electrocardiography Algorithm design and analysis Accuracy Signal processing algorithms Compressed sensing Vectors Matching pursuit algorithms multi-channel ECG compressive sensing cosparsity greedy analysis pursuit |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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