ArticlePloS one2021
A computationally efficient dynamic model of human epicardial tissue.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Multiscale Electrophysiological Remodeling in Ischemic Heart Failure: Simulation Analysis of Ventricular Ectopic Activation.Biomedicines · 2026Article
- Exploring wave propagation dynamics in heterogeneous excitable media: effects of intermittent cellular inactivation.Frontiers in physiology · 2026Article
- What is the best pulse shape for pacing purposes?Frontiers in physiology · 2025Article
- A smoothed boundary bidomain model for cardiac simulations in anatomically detailed geometries.PloS one · 2023Article
- Diffuse fibrosis and repolarization disorders explain ventricular arrhythmias in Brugada syndrome: a computational study.Scientific reports · 2022Article
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2 authors.
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Abstract
We present a new phenomenological model of human ventricular epicardial cells and we test its reentry dynamics. The model is derived from the Rogers-McCulloch formulation of the FitzHugh-Nagumo equations and represents the total ionic current divided into three contributions corresponding to the excitatory, recovery and transient outward currents. Our model reproduces the main characteristics of human epicardial tissue, including action potential amplitude and morphology, upstroke velocity, and action potential duration and conduction velocity restitution curves. The reentry dynamics is stable, and the dominant period is about 270 ms, which is comparable to clinical values. The proposed model is the first phenomenological model able to accurately resemble human experimental data by using only 3 state variables and 17 parameters. Indeed, it is more computationally efficient than existing models (i.e., almost two times faster than the minimal ventricular model). Beyond the computational efficiency, the low number of parameters facilitates the process of fitting the model to the experimental data.
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