Abstract
Wireless patient monitoring is an active research area with the goal of ubiquitous health care services. This study presents a novel means of exploiting the distributed source coding (DSC) in low-complexity compression of ECG signals. We first convert the ECG data compression to an equivalent channel coding problem and exploit a linear channel code for the DSC construction. Performance is further enhanced by the use of a correlation channel that more precisely characterizes the statistical dependencies of ECG signals. Also proposed is a modified BCJR algorithm which performs symbol decoding of binary convolutional codes to better exploit the source's a priori information. Finally, a complete setup system for online ambulatory ECG monitoring via mobile cellular networks is presented. Experiments on the MIT-BIH arrhythmia database and real-time acquired ECG signals demonstrate that the proposed system outperforms other schemes in terms of encoder complexity and coding efficiency. Copyright © 2014 The Institute of Electronics, Information and Communication Engineers.
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CITATION STYLE
Wu, H. T., Tsai, W. Y., & Chang, W. W. (2014). Distributed source coding for real-time ECG signal monitoring. IEICE Transactions on Information and Systems, E97-D(8), 2157–2165. https://doi.org/10.1587/transinf.E97.D.2157
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