Detection of Myocardial Ischemia from ECG Signal Using Max30001

Among the commonly occurring medical emergencies such as heart attack, arrhythmia, valve diseases and high blood pressure, reduction in blood flow to the heart prevents the reception of sufficient oxygen to the heath muscles known as myocardial ischemia caused the partial of complete blockage of coronary arteries. Myocardial ischemia prevents the heart muscles to pump the blood efficiently that can ultimately lead to the heart attack or may cause abnormal heart rhythms. Electrocardiogram (ECG) an electrical activity of the heart is mostly used by the cardiologist for diagnosing MI patients. Identifying the MI manually is time consuming and a possibility of misinterpretation exists to the changes in the patient ECG. An automated method for the detection of MI pattern in the ECG is proposed using wavelet transform. It is observed that the difference in the height of PR segment and J-point allows to distinguish between a normal ECG and abnormal MI ECG. Furthermore, this study also finds that there is a significant difference in the J-point, R-peak amplitude and ST- wave of the MI patient than the normal healthy person when the patients ECG is recorded using MAX30001.