ISSN: 2329-9495
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Department of Electronics and Communication Engineering, Central Polytechnic College, Chennai, Tamil Nadu, India
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