ECG Data Analysis using CNN and SVM

Electrocardiogram (ECG) is a P, QRS and T wave signifying the electrical activity of the heart. Feature extraction and segmentation in ECG plays a major part in analysing most of the cardiac disease. According to a recent study by the Indian Council of Medical Research (ICMR) near about 25% of deaths between the ages of 25-69 years cause due to different heart-related problems. This paper provides a comprehensive review of the different techniques used by the researchers for diagnosing Arrhythmias and abstract view of the proposed system that we are going to implement with increasing accuracy using CNN. The system predicts the type of arrhythmia based on real-time ECG signals. The goal of this paper is to analyse, examine, evaluate, and make a summary of various approaches prediction of heart disease.