Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (6A): 220300094-11.doi: 10.11896/jsjkx.220300094

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Review of Research on Denoising Algorithms of ECG Signal

HOU Yanrong1, LIU Ruixia2, SHU Minglei2, CHEN Changfang2, SHAN Ke2   

  1. 1 School of Mathematics and Statistics,Qilu University of Technology(Shandong Academy of Sciences),Jinan 250353,China;
    2 Shandong Artificial Intelligence Institute,Qilu University of Technology(Shandong Academy of Sciences),Jinan 250014,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:HOU Yanrong,born in 1999,postgra-duate.His main research interests include intelligent system and its application in engineering, and medical signal processing. LIU Ruixia,born in 1976,associate researcher,master supervisor.Her main research interests include signal processing and medical artificial intelligence.
  • Supported by:
    National Key R&D Program of China(2018YFB1404500).

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Abstract: One of the most common signal processing problems with the electrocardiogram(ECG),an important indicator for identifying cardiac abnormalities in humans,is the elimination of unwanted noise.These noises can distort the clean signal,which can affect the diagnosis and analysis of the human heart.This paper reviews five different frameworks of ECG signal denoising techniques and the latest research results within these frameworks,and finally summarizes the best noise reduction models in last five years and compares them by performance evaluation criteria such as signal-to-noise ratio.The comparison shows that the deep learning models show good performance in ECG denoising,whether based on single noise or composite noise.Finally,the problems with the current denoising model are discussed and an outlook on the next step of the research is given.

Key words: Electrocardiogram(ECG), Deep learning, Denoising, Signal-to-noise ratio

CLC Number: 

  • TP301.6
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