{"title":"Integration of electromechanical feedback in cardiac electrophysiology: A multiphysics approach using finite element analysis","authors":"Chen Yang , Yidi Cao , Min Xiang","doi":"10.1016/j.chaos.2025.116819","DOIUrl":null,"url":null,"abstract":"<div><div>Mathematical modeling of cardiac electrophysiology and mechanical feedback plays a critical role in computational medicine. Traditional electrophysiological models focus primarily on the electrical components of excitation-activated transmembrane ion currents. Additionally, electromechanical feedback modeling accounts for the effects of stretch-induced components. In this study, we introduce a novel modular finite element framework for coupled multiphysics cardiac electromechanical feedback modeling. The framework integrates the bidomain model with the Fitzhugh-Nagumo (FHN) model for electrophysiological modeling, and couples it with a dimensional mapping of stretch-induced ion currents. The resulting framework effectively simulates electrophysiological (EP) signal output, incorporating electromechanical feedback. After obtaining the fiber, sheet, and perpendicular to the sheet directions of the myocardium, cardiac mechanical contraction is simulated by additive decomposition of the active stress, varying along these three directions by different percentages in accordance with the changes in transmembrane potential. We performed numerical simulations on realistic atrial-torso and ventricular-torso geometries. By comparing the results of standard 12‑lead electrocardiogram (ECG) and body surface potential maps (BSPMs), it is evident that the impact of cardiac electromechanical modeling on EP output should not be overlooked.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"199 ","pages":"Article 116819"},"PeriodicalIF":5.6000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chaos Solitons & Fractals","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S096007792500832X","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Mathematical modeling of cardiac electrophysiology and mechanical feedback plays a critical role in computational medicine. Traditional electrophysiological models focus primarily on the electrical components of excitation-activated transmembrane ion currents. Additionally, electromechanical feedback modeling accounts for the effects of stretch-induced components. In this study, we introduce a novel modular finite element framework for coupled multiphysics cardiac electromechanical feedback modeling. The framework integrates the bidomain model with the Fitzhugh-Nagumo (FHN) model for electrophysiological modeling, and couples it with a dimensional mapping of stretch-induced ion currents. The resulting framework effectively simulates electrophysiological (EP) signal output, incorporating electromechanical feedback. After obtaining the fiber, sheet, and perpendicular to the sheet directions of the myocardium, cardiac mechanical contraction is simulated by additive decomposition of the active stress, varying along these three directions by different percentages in accordance with the changes in transmembrane potential. We performed numerical simulations on realistic atrial-torso and ventricular-torso geometries. By comparing the results of standard 12‑lead electrocardiogram (ECG) and body surface potential maps (BSPMs), it is evident that the impact of cardiac electromechanical modeling on EP output should not be overlooked.
期刊介绍:
Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.