Heartbeat classification using deep residual convolutional neural network from 2-lead electrocardiogram.

Journal: Journal of electrocardiology
Published Date: Nov 22, 2019

Abstract

BACKGROUND: The electrocardiogram (ECG) has been widely used in the diagnosis of heart disease such as arrhythmia due to its simplicity and non-invasive nature. Arrhythmia can be classified into many types, including life-threatening and non-life-threatening. Accurate detection of arrhythmic types can effectively prevent heart disease and reduce mortality.

Authors

  • Zhi Li
    Department of Nursing, Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Traditional Chinese Medicine, Zhongshan, China.
  • Dengshi Zhou
    College of Electronic and Information Engineering, Sichuan University, Chengdu 610065, China.
  • Li Wan
    School of Software Engineering, Southeast University, Nanjing, 211189, China.
  • Jian Li
    Fujian Key Laboratory of Traditional Chinese Veterinary Medicine and Animal Health, College of Animal Science, Fujian Agriculture and Forestry University, Fuzhou, China.
  • Wenfeng Mou
    College of Electronic and Information Engineering, Sichuan University, Chengdu 610065, China.

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