Algorithmization of Electrostatic Model for Solving the Direct Problem of Electrography
Tagirbek Gaidarbekovich Aslanov1, Naur Zamirovich Ivanov1, Shamil Shamil`evich Anudinov1 & Tatiana Vladimirovna Karlova1 Show affiliations
- World-Class Scientific Center "Digital Biodesign and Personalized Healthcare", Institute of Design and Technology Informatics, Russian Academy of Sciences, Vadkovsky Lane, 18, Building 1A, Moscow, Russia
Journal of Computer Science, Volume 21, Issue 4, pp. 869–882 · doi.org/10.3844/jcssp.2025.869.882
Abstract
An analysis of the creation and implementation of algorithms to control cardiological processes occurring in the cardiovascular system using software and hardware diagnostic systems is a required activity. This study considers ways to improve the methods of medical data processing using electronic diagnostic systems, relying on existing methods of mathematical simulation of human body states. This study describes the development of a method that solves the direct problem of electrical cardiography by using complete electrostatic simulations. For this purpose, the selection of key characteristics of simulations of anatomical features and physiology of an organism is used by considering the bioelectrical data obtained experimentally. This study describes the basic relations to characterize the electric field and considers the electrophysical properties of biological tissues. The simulation considered the specifics of the functioning of the proposed method, which imitates the activity of the heart muscle. A novel algorithm is proposed that allows for the detection of myocardial pathological changes that arise during diagnostic procedures, utilizing the reconstructed trajectory of single charge movement. An in-depth study of the electric fields of the controlled object using multipole dispersions was conducted, and the impact of the level of multipole dispersions on the reliability and error of the simulation results was analyzed. The proposed simulation does improve the reliability of the parameters obtained during diagnosis using electronic cardiac systems. The implementation of calculation methods for electrophysiological signals based on this model has the potential to facilitate diagnostic procedures even in the presence of undetected pathologies, offering a valuable complement to traditional diagnostic techniques.
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Aslanov, T. G., Ivanov, N. Z., Anudinov, S. S. & Karlova, T. V. (2025). Algorithmization of Electrostatic Model for Solving the Direct Problem of Electrography. Journal of Computer Science, 21(4), 869–882. https://doi.org/10.3844/jcssp.2025.869.882
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