Research on ECG Denoising method Based on Empirical Mode Decomposition and Wavelet Transform

The measured ECG inevitably has some strong interference and noise. Effective ECG signals are extracted from strong background interference and noise, which is an important basis for judging various arrhythmia, myocardial infarction and other diseases. After a comprehensive comparison of the effects of several denoising methods, an empirical mode decomposition (EMD) combined with wavelet soft threshold method is proposed in this paper. Firstly, the ECG signal is decomposed into multi-layer IMF modal components by EMD decomposition. Then the high-frequency modal component of the noise signal was processed by wavelet threshold, and the useful component of the ECG signal was extracted from the high-frequency IMF modal component. Finally, After reconstruction by the useful signals obtained from high-frequency IMFs components and the modal components of low-frequency IMFs, the denoised ECG signal was obtained. The results show that this method is superior to EMD, wavelet transform and band-pass filtering combined with the denoising method, and has the advantages of high SNR, low RMSE and high coefficient correlation, which is suitable for ECG original signal denoising.