An ECG signal de-noising approach based on wavelet energy and sub-band smoothing filter

Dengyong Zhang, Shanshan Wang, Feng Li, Jin Wang, Arun Kumar Sangaiah, Victor S. Sheng, Xiangling Ding

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


Electrocardiographic (ECG) signal is essential to diagnose and analyse cardiac disease. However, ECG signals are susceptible to be contaminated with various noises, which affect the application value of ECG signals. In this paper, we propose an ECG signal de-noising method using wavelet energy and a sub-band smoothing filter. Unlike the traditional wavelet threshold de-noising method, which carries out threshold processing for all wavelet coefficients, the wavelet coefficients that require threshold de-noising are selected according to the wavelet energy and other wavelet coefficients remain unchanged in the proposed method. Moreover, The sub-band smoothing filter is adopted to further de-noise the ECG signal and improve the ECG signal quality. The ECG signals of the standardMIT-BIH database are adopted to verify the proposed method usingMATLAB software. The performance of the proposed approach is assessed using Signal-To-Noise ratio (SNR), Mean Square Error (MSE) and percent root mean square difference (PRD). The experimental results illustrate that the proposed method can effectively remove noise from the noisy ECG signals in comparison to the existing methods.

Original languageEnglish
Article number4968
JournalApplied Sciences (Switzerland)
Issue number22
StatePublished - Nov 1 2019


  • Discrete wavelet transform
  • ECG
  • Smoothing filter
  • Wavelet energy


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