Implementation of compressive sensing in ECG and EEG signal processing

被引:10
|
作者
Zhang H.-X. [1 ]
Wang H.-Q. [1 ]
Li X.-M. [1 ]
Lu Y.-H. [1 ]
Zhang L.-K. [2 ]
机构
[1] School of Electronic Engineering, Beijing University of Posts and Telecommunications
[2] Translation Group, Certain Department of the Second Artillery Force of PLA
基金
中国国家自然科学基金;
关键词
CS; ECG; EEG;
D O I
10.1016/S1005-8885(09)60535-5
中图分类号
学科分类号
摘要
The purpose of this paper is to exploit compressive sensing (CS) method in dealing with electrocardiography (ECG) and electroencephalography (EEG) signals at a high compression ratio. In order to get sparse data of ECG and EEG signals before being compressed, a combined scheme was presented by using wavelet transform and iterative threshold method; then, compressive sensing is executed to make the data compressed. After doing compressive sensing, Bayesian compressive sensing (BCS) is used to reconstruct the original signals. The simulation results show that compressive sensing is an effective method to make data compressed for ECG and EEG signals with high compression ratio and good quality of reconstruction. Furthermore, it shows that the proposed scheme has good denoising effects. © 2010 The Journal of China Universities of Posts and Telecommunications.
引用
收藏
页码:122 / 126
页数:4
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