Angiology: Open Access
Open Access

Department of Electronics and Communication Engineering, Saveetha Engineering College, Chennai, Tamil Nadu, India

Publications

• Research Article   
  Enhancing Early Detection of Cardiovascular Diseases through Deep Learning-Based ECG Signal Classification
  Author(s): Immaculate Joy Selvam*, Moorthi Madhavan and Senthil Kumar Kumaraswamy
  
  The global impact of Cardiovascular Diseases (CVDs) is profound and requires urgent attention. Accurately classifying heartbeats is essential for assessing cardiac function and detecting any irregularities. Electrocardiograms (ECGs) play a critical role in diagnosing CVD by providing graphical representations of the heart's electrical activity. In this study, Deep Learning (DL) models are employed to automatically categorize ECG data into different classifications, including normal, conduction disturbance, ST/T change, myocardial infarction, and hypertrophy. To achieve this classification task, we utilize the PTB-XL database, which eliminates the need for real-time patient data collection by providing a comprehensive collection of ECG recordings. To aid in the accurate classification of ECG data, we suggest a hybrid DL method that makes use of Convolutional Neural.. View More»
  DOI: 10.35248/2329-9495.23.11.396

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