Detection and classification of electrocardiography using hybrid deep learning models.

Journal: Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese
Published Date: Aug 30, 2024

Abstract

OBJECTIVE: Electrocardiography (ECGs) has been a vital tool for cardiovascular disease (CVD) diagnosis, which visually depicts the heart's electrical activity. To enhance automatic classification between normal and diseased ECG, it is essential to extract consistent and qualitative features.

Authors

  • Immaculate Joy Selvam
    Department of Electronics and Communication Engineering, Saveetha Engineering College, Thandalam, Chennai, 602105, India. Electronic address: immaculatejoy@saveetha.ac.in.
  • Moorthi Madhavan
    Department of Biomedical Engineering, Saveetha Engineering College, Thandalam, Chennai, 602105, India. Electronic address: moorthi@saveetha.ac.in.
  • Senthil Kumar Kumarasamy
    Department of Electronics and Communication Engineering, Central Polytechnic College, Tharamani, Chennai, 600113, India. Electronic address: ksenthilkumar.ece.phd@gmail.com.

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