ECG Signal Classification Using Machine Learning and Deep Learning: A Unified Framework
Keywords:
Electrocardiogram (ECG), Machine Learning (ML), Deep Learning (DL), Signal Classification, Cardiovascular Disease, Automated DiagnosisAbstract
The accurate classification of electrocardiogram (ECG) signals is vital for the early detection and diagnosis ofcardiovascular diseases. This study evaluates and compares the performance of various Machine Learning (ML) andDeep Learning (DL) models in classifying ECG signals into normal and abnormal categories. A comprehensive set ofmodels, including logistic regression, support vector machines (SVM), random forests, k-nearest neighbors (KNN),
References
World Health Organization. (2023). Cardiovascular diseases (CVDs). https://www.who.int/news-room/factsheets/detail/cardiovascular-diseases-(cvds)
Singh, A. K., & Krishnan, S. (2023). ECG signal feature extraction trends in methods and applications. Biomedical Engineering Online, 22(1), 22. https://doi.org/10.1186/s12938-023-01064-y
