Authors : Pulkeshini Vishal Taksande, Abhinav Muley
DOI : 10.46335/IJIES.2024.9.7.3
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Abstract – The main focus of this paper is to review and analyze the various techniques used to analyze Electrocardiogram, ECG using different Machine Learning Techniques. Electrocardiogram is pivotal in the diagnosis and management of cardiovascular diseases, which is the leading cause of mortality. The emergence of machine learning technologies has transformed the field of biomedical signal processing attempting promising avenues for enhancing ECG analysis accuracy and efficiency. This review paper provides a comprehensive study of the various machine-learning models applied in ECG analysis, highlighting their methodologies, strengths, challenges, and applications. The models generally used for ECG analysis are Convolutional Neural Network (CNN), deep neural networks, Long-Short Term Memory (LSTM), and Recurrent Neural Networks(RNNs).
