Methodological Approach to Developing a Model of Interference-Free Processing of Multichannel Records of the Electrical Cardiological Impulse to Determine Episodes of Cardiac Muscle Ischemia

This study considered a set of topical issues aimed at improving the methodology of the early recognition of episodes of myocardial ischemia. It aims to solve a set of problems in the substantiation and development of a methodological approach for building a model of interference-free processing of multichannel electrocardio signal recordings. Based on theoretical and experimental studies, this will create new methods of increased interference resistance to recognize the phases of cardiac muscle ischemia. This study focused on the development of multiple simulations of changes in electrical cardiac impulse in several branches during the progress of cardiac muscle ischemia, including the influence of muscle noise. This study analyzed existing methodological approaches for the early detection of Ischemic Heart Disease (IHD) and electrocardio signal processing, analysis and classification, which are the most promising methods for detecting and classifying myocardial ischemia. The relevance of a technique for detecting IHD phases using multiple simulations of electrical cardiac impulses and their change in ST segments in different branches, considering the combined effect of the noise component, was substantiated. The importance of its implementation within the framework of an operational automated system for detecting life-threatening episodes of myocardial ischemia has been emphasized. The proposed solution makes it possible to rely on the automatic and interference-resistant detection of IHD phases in interference-distorted segments of electrical cardiac impulses. The results demonstrated the practical coincidence of the experimentally and theoretically obtained data on the probability of decision-making for one of the IHD phases. A study undertaken in conjunction with the I.M. Sechenov First Moscow State Medical University, as part of a world-class research centre, revealed that the discrepancy between practical and theoretical data was less than 5%.