Research on ECG De-noising Method Based on Ensemble Empirical Mode Decomposition and Wavelet Transform Using Improved Threshold Function_Journal of Biomedical Engineering

Authors：

YELinlin ,  YANGDan , WANGXu

School of Information Science and Engineering, Northeastern University, Shenyang 110819, China;

Corresponding author：

YANGDan, Email: yangdan@ise.neu.edu.cn

Keywords：

electrocardiogram; ensemble empirical mode decomposition; intrinsic mode function; improved threshold function; MIT-BIH

DOI：

10.7507/1001-5515.20140106

Video：

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A de-noising method for electrocardiogram (ECG) based on ensemble empirical mode decomposition (EEMD) and wavelet threshold de-noising theory is proposed in our school. We decomposed noised ECG signals with the proposed method using the EEMD and calculated a series of intrinsic mode functions (IMFs). Then we selected IMFs and reconstructed them to realize the de-noising for ECG. The processed ECG signals were filtered again with wavelet transform using improved threshold function. In the experiments, MIT-BIH ECG database was used for evaluating the performance of the proposed method, contrasting with de-noising method based on EEMD and wavelet transform with improved threshold function alone in parameters of signal to noise ratio (SNR) and mean square error (MSE). The results showed that the ECG waveforms de-noised with the proposed method were smooth and the amplitudes of ECG features did not attenuate. In conclusion, the method discussed in this paper can realize the ECG de-noising and meanwhile keep the characteristics of original ECG signal.

Citation： YELinlin, YANGDan, WANGXu. Research on ECG De-noising Method Based on Ensemble Empirical Mode Decomposition and Wavelet Transform Using Improved Threshold Function. Journal of Biomedical Engineering, 2014, 31(3): 567-571. doi: 10.7507/1001-5515.20140106 Copy

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9.	金晶晶,王旭,吴雪,等.基于改进阈值函数的体震信号平移不变去噪[J].东北大学学报,2009,30(3):333-336.

1. TRACEY B H, MILLER E L. Nonlocal means denoising of ECG signals[J]. IEEE Trans Biomed Eng, 2012, 59(9):2383-2386.
2. WANG A D, LIU L, WEI Q. An adaptive morphologic filter applied to ECG denoising and extraction of R peak at real-time[J]. AASRI Procedia, 2012, 1:474-479.
3. SMITAL L, VÍTEK M, KOZUMPLÍK J, et al. Adaptive wavelet Wiener filtering of ECG signals[J]. IEEE Trans Biomed Eng, 2013, 60(2):437-445.
4. SHARMA L N, DANDAPAT S, MAHANTA A. ECG signal de-noising using higher order statistics in Wavelet sub bans[J]. Biomed Signal Process Control, 2010, 5(3):214-222.
5. PAL S, MITRA M. Empirical mode decomposition based ECG enhancement and QRS detection[J]. Comput Biol Med, 2012, 42(1):83-92.
6. KARAGIANNIS A, CONSTANTINOU P. Noise-assisted data processing with empirical mode decomposition in biomedical signals[J]. IEEE Trans Inf Technol Biomed, 2011, 15(1):11-18.
7. CHANG K M, LIU S H. Gaussian noise filtering from ECG by wiener filter and ensemble empirical mode decomposition[J]. J Signal Process Syst, 2011, 64:249-264.
8. WANG C L, ZHANG C L, ZHANG P T. Denoising algorithm based on wavelet adaptive threshold[J]. Physics Procesia, 2012, 24(Part A):678-685.
9. 金晶晶,王旭,吴雪,等.基于改进阈值函数的体震信号平移不变去噪[J].东北大学学报,2009,30(3):333-336.

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