Cardiac Arrhythmia Diagnosis System from Electrocardiogram Signal using Machine Learning Approach

Abstract

People nowadays come cross lot of life threatening diseases. One of the crucial diseases is cardiac disease. Cardiac arrhythmia is a disorder which needs timely diagnosis for avoiding sudden cardiac arrest. In Arrhythmia, the heartbeat is too irregular, too slow, or too fast. The Cardiac diseases are monitored using electrocardiogram (ECG). The major objective of this paper is to discriminate between the normal and diseased persons using machine learning approach. The Cardiac Arrhythmia Diagnosis system involves the following processes such as feature extraction, feature selection and classification. Feed forward Neural Network is proposed in this work and results are compared with support vector machine.