Cardiovascular diseases are very important to detect as early as possible because it leads to death in the world, and Myocardial Infarction (MI) is very dangerous one among those diseases. Patient monitoring for an early detection of MI is most important to alert medical assistance and increase the vital prognostic of patients. In this paper, trying to detect the Myocardial Infarction, where it is exactly and up to which extent. PhysioNet challenge 2007 Database the Body surface potential map database which consists of ECG of normal and myocardial infarcted patients is used. Since the data available is less, Bilinear Interpolation is used to generate data from the existing. PhysioNet challenge 2007 database has BSPM data. Data is all about four patients with MI, where two patient’s data are used as training set to determine rules, and two other patients for testing set. The Myocardial Infarction is detected using some rule and threshold values using Artificial Neural Network. The accuracy might be increased when one patient data follows multiple rules and compared by other patients data.