Analysis, Detection and Classification of ECG Signal for Myocardial Infarction using Simple Cross-correlation Function

Analysis of standard clinical electrocardiogram signal is one of the basic routine tests for preliminary screening of cardiac disorders. This work deals with classification of normal and IMI (Inferior Myocardial Infarction) ECGs and presents a method for analysis of Electrocardiogram (ECG) patterns using Cross Correlation. The application of cross correlation to two ECG beats and the cross examination of the results reveals the localized similarities of the signals. In this paper two novel parameters are used for the analysis and classification of ECG signals; they are the maximum and average value of the cross correlated spectrum. Also, in this work, two methods are developed for the classification of MI: Method 1 directly uses the extracted single beat of ECG signal for further processing whereas Method 2 uses the average value of corresponding coefficients in the first 5 beats of the ECG signal as the single beat sample for further processing. The recognition score obtained for first method is 80% and that for second method is 91% . Keywords— Electrocardiogram, QRS complex, Cross correlation, Myocardial infarction