Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals.

Journal: BMC medical informatics and decision making
Published Date: Oct 19, 2023

Abstract

BACKGROUND: Cardiac arrhythmia is a cardiovascular disorder characterized by disturbances in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically, ECG machines are utilized to diagnose and monitor cardiac arrhythmia noninvasively. Since ECG signals are dynamic in nature and depict various complex information, visual assessment and analysis are time consuming and very difficult. Therefore, an automated system that can assist physicians in the easy detection of arrhythmia is needed.

Authors

  • Yared Daniel Daydulo
    Department of Biomedical Engineering, Dilla University Referral Hospital, Dilla, Ethiopia.
  • Bheema Lingaiah Thamineni
    School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia. bheema.lingaiah@ju.edu.et.
  • Ahmed Ali Dawud
    School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia. ahme8002@gmail.com.

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