Performance Analysis of Support Vector Machine and Neural Networks in Detection of Myocardial Infarction

One of the most common form of cardiac abnormality is Myocardial Infarction (heart attack) arises when the artery connecting the heart is blocked and there is no sufficient blood or oxygen, which makes the cells present in that region of the heart to die. This paper aims to process and classify an ECG signal as healthy subject or subject diagnosed with Myocardial Infarction (MI) using Artificial Neural Networks (ANN) and SVM (Support Vector Machine). LIBSVM1 is utilized for the classification with SVM and backpropogation artificial neural networks with varying hidden layers and nodes are also implemented for performance analysis.