A CNN Model for Cardiac Arrhythmias Classification Based on Individual ECG Signals.

Journal: Cardiovascular engineering and technology
Published Date: Jan 3, 2022

Abstract

PURPOSE: Wearable devices in the scenario of connected home healthcare integrated with artificial intelligence have been an effective alternative to the conventional medical devices. Despite various benefits of wearable electrocardiogram (ECG) device, several deficiencies remain unsolved such as noise problem caused by user mobility. Therefore, an insensitive and robust classification model for cardiac arrhythmias detection system needs to be devised.

Authors

  • Yuan Zhang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Sen Liu
    Automotive Data Center, China Automotive Technology & Research, Tianjin, 300300, China.
  • Zhihui He
    Department of Pediatric Respiration, Chongqing Ninth People's Hospital, Chongqing, 400700, China.
  • Yuwei Zhang
    Institute of Biomaterials and Biomedical Engineering , University of Toronto , 164 College Street , Toronto , Ontario M5S 3G9 , Canada.
  • Changming Wang
    Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China. superwcm@163.com.

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