Quantifying Heartbeat Micro-Fragmentations Post-Myocardial Infarction Using Wavelet Entropy and Complexity

Abstract

Cardiovascular diseases are recognized as one of the leading causes of mortality, with myocardial infarction (MI) being a critical condition that disrupts the heart’s electrical conduction due to myocardial tissue damage. The aim of this study is to examine two key phases following MI, excluding ventricular tachycardia (VT) and/or ventricular fibrillation (VF): the healing phase (up to one week after, referred to as MI7) and the healed phase (more than two months after, referred to as MI60). During these phases, severe complications, such as sudden cardiac death, may occur. Electrocardiograms (ECGs) of healthy individuals (CT RL) and MI patients in the MI7 and MI60 stages were analyzed, using data from the PTB and PTB XL databases. The analysis specifically examined the presence of heartbeat micro-fragmentations, known as µf QRS, associated with MI, and employed indicators based on Shannon wavelet entropy (H) and Statistical Complexity (C), derived from Continuous Wavelet Transform. Receiver Operating Characteristic (ROC) curves were used to assess these indicators, yielding significant results validated across the databases and their combination. Entropy and Complexity indicators proved to be promising tools for evaluating morphological changes in the heartbeats of post-MI patients. The findings support the usefulness of these indicators in µf QRS analysis and highlight their potential application in both clinical and medical research settings.