中国邮电高校学报(英文) ›› 2010, Vol. 17 ›› Issue (6): 122-126.doi: 10.1016/S1005-8885(09)60535-5

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Implementation of compressive sensing in ECG and EEG signal processing

张洪欣   

  1. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • 收稿日期:2010-04-09 修回日期:2010-07-13 出版日期:2010-12-30 发布日期:2010-12-06
  • 通讯作者: 张洪欣 E-mail: hongxinzhang@bupt.edu.cn
  • 基金资助:

    国家自然基金课题;中央高校基本科研业务费专项资金

Implementation of compressive sensing in ECG and EEG signal processing

  1. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2010-04-09 Revised:2010-07-13 Online:2010-12-30 Published:2010-12-06
  • Supported by:

    ;Fundamental Research Funds for the Central Universities

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.

关键词:

CS, ECG, EEG

Abstract:

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.

Key words:

CS, ECG, EEG