AUTOMATED IDENTIFICATION OF MYOCARDIAL INFRACTION USING HARMONIC PHASE DISTRIBUTION PATTERN OF ECG DATA
Astha Mehta, Swapnil Aryan Sinha, Ankita Singh
The proposed project consists of the integration of automated ECG analysis techniques for the early detection of myocardial infarction, known as heart attack. It consists of easier and compact way of the detection compared to the already existing models which use complex computations and classifiers to detect MI. The wave sequence consists of P, QRS and T waves which form a complete cardiac cycle. These components are extracted during the analysis of the wave. These components, then, help in distinguishing the heart abnormalities.