Denoising Method of ECG Signal with Power Threshold Function Under Wavelet Transform and Smoothing Filter

EasyChair Preprint 6831

Abstract

An electrocardiogram (ECG) is an important tool for doctors to diagnose heart diseases. It is an electrical signal that evolves from the heart and changes over time. It is susceptible to interference from various low-frequency and high-frequency noises. This paper proposes a new adaptive power threshold function to achieve the denoising of ECG signals. On the basis of wavelet transformation and smooth decomposition, the power threshold function is used to perform adaptive threshold denoising on the decomposed signal with high frequency noise. The signal is reconstructed from the denoised high frequency components and useful components. The coefficients of the remaining layers are set to zero. Taking the ECG signal in the MIT-BIH ECG database as the original data, adding different degrees of Gaussian white noise for experimental analysis, it is proved from the quantitative and qualitative aspects that the proposed method has superiority in removing the noise of the ECG signal. The noise effect is better than the traditional threshold function denoising method.

Keyphrases: ECG signal, Power Threshold Function, Smooth Decomposition, threshold denoising, threshold method, wavelet transform

@booklet{EasyChair:6831,
  author    = {Chunyang Wu and Beiwei Zhang and Jinliang Liu and Jinhai Li},
  title     = {Denoising Method of ECG Signal with Power Threshold Function Under Wavelet Transform and Smoothing Filter},
  howpublished = {EasyChair Preprint 6831},
  year      = {EasyChair, 2021}}