A novel ECG signal denoising method based on Hilbert-Huang Transform

This paper aims to explore a method about electrocardiogram (ECG) signal denoising based on Hilbert-Huang Transform. The empirical mode decomposition method can decompose the noisy signal into a number of Intrinsic Mode Functions. Energy analysis is conducted on the IMFs to find out the boundary between the noise-dominated IMFs and ECG signal dominated IMFs accurately. The most noisy IMFs are denoised by using Donoho soft-threshold denoising method. The denoised high frequency IMFs are added to the low frequency IMFs to reconstruct the original signal. The simulation experiments show that this method is simpler than the wavelet denoising method. It is not necessary to choose wavelet basis or determine the number of layers and the threshold. The proposed method can come close to or achieve the best level of wavelet denoising.