The Limb Leads ECG Signal Analysis in Inferior Myocardial Infarction Patients by Rule Base

Cardiovascular disease is one of the most serious diseases in the world. The electrocardiogram is signal showing the cardiac electrical activity and use to diagnostic of Myocardial Infarction which detects abnormal wave patterns. The anatomic location of the infarcted areas; inferior, anterior, lateral is recommended for treatment decision. Electrocardiogram can predict the risk of patients and guide physician's decision making. This research purposes a limb leads; I, II and III electrocardiogram analysis algorithm using Wavelet transform to detect waveform and rule base to classify Inferior Myocardial Infarction patients. The contribution of this research is investigating the lead which relate to the Inferior infarcts, anatomic location of the infarcted area which not found in any researches. The processes in ECG signal analysis are noise elimination and baseline wander removal, R peak Detection, QRS Complex Detection, ST-segment Detection and Inferior Myocardial Infarction Classification. The results show that the Inferior Myocardial Infarction Classification algorithm has 85% accuracy. Lead III is the most relevant to inferior infarct area, 86.96% relate to inferior infarct. Second is Lead II, 47.83% relate to inferior infarct. Lead I is the less relevant to inferior infarct area, 13.04^% relate to inferior infarct.