A Novel Adaptive Wavelet Thresholding with Identical Correlation Shrinkage Function for ECG Noise Removal  

作　　者：HE Hong TAN Yonghong 

机构地区：[1]College of Information, Mechanical and Electrical Engineering, Shanghai Normal University

出　　处：《Chinese Journal of Electronics》2018年第3期507-513,共7页电子学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.61571302,No.61371145,No.61671303);Industry-education-research Project of Shanghai Normal University(No.DCL201704);the Project of the Science and Technology Commission of Shanghai(No.18070503000)

摘　　要：On the basis of wavelet theory, a novel Adaptive wavelet thresholding method(AWT) is proposed for the ECG signal enhancement. The best base wavelet for ECG signal filtering can be automatically obtained through the cross correlation coefficient and the energy to entropy ratio. The variable universal threshold(Var Universal) is applied to different decomposition level so as to suppress diverse noise. To achieve a smooth cut-off transition, an identical correlation shrinkage function(Ico Shrinkage) is also adopted in the AWT according to its correlation coefficients with the hard thresholding and the soft thresholding. The performance of AWT is compared with four threshold approaches and six shrinkage functions, respectively, on the basis of 150 practical ECG signals of 30 subjects. The filtering results reveal that the AWT can adaptively choose an optimal base wavelet for a specific ECG signal. With the Var Universal threshold and Ico Shrinkage,the AWT obtains the better filtering results than the other compared methods.On the basis of wavelet theory, a novel Adaptive wavelet thresholding method（AWT） is proposed for the ECG signal enhancement. The best base wavelet for ECG signal filtering can be automatically obtained through the cross correlation coefficient and the energy to entropy ratio. The variable universal threshold（Var Universal） is applied to different decomposition level so as to suppress diverse noise. To achieve a smooth cut-off transition, an identical correlation shrinkage function（Ico Shrinkage） is also adopted in the AWT according to its correlation coefficients with the hard thresholding and the soft thresholding. The performance of AWT is compared with four threshold approaches and six shrinkage functions, respectively, on the basis of 150 practical ECG signals of 30 subjects. The filtering results reveal that the AWT can adaptively choose an optimal base wavelet for a specific ECG signal. With the Var Universal threshold and Ico Shrinkage,the AWT obtains the better filtering results than the other compared methods.

关 键 词：Wavelet decomposition Shrinkage function Noise filtering Adaptability 

分 类 号：R318[医药卫生—生物医学工程] TN911.4[医药卫生—基础医学]