A Study of Feature Extraction Algorithms for ST-Elevation, R/S Amplitude, and T-Wave Inversion in Detecting Myocardial Infarction on Electrocardiogram Signals

Myocardial Infarction (MI) significantly contributes to global mortality, emphasizing the need for early detection. This study evaluates the diagnostic performance of three ECG feature extraction methods: ST-elevation, R/S amplitude, and T-wave inversion. Using the PTB Diagnostic ECG Database, each feature was analyzed independently and in combinations to determine their potential for MI detection. Preprocessing included digital filtering to enhance signal quality. Results indicate that combining ST-elevation, R/S amplitude, and T-wave inversion, with an accuracy of 86.92%, sensitivity of 90.27%, specificity of 73.12%, and F1-score of 80.18%. While ST-elevation independently demonstrates strong specificity, feature combinations improve sensitivity and provide a balanced diagnostic outcome. These findings highlight the value of integrating ECG features to overcome limitations of single-feature methods.