Key result
Dual adaptive explicit method improves computational efficiency over standard operator splitting while preserving accuracy.
Why the study?
Fully explicit methods for solving the decoupled monodomain model have lower memory footprint and higher scalability but are limited by conditional stability.
A novel dual adaptive explicit time integration algorithm improves computational efficiency while preserving accuracy for solving the cardiac monodomain equation in in-silico models.
May enable faster cardiac electrophysiology modeling; leaves open validation in clinical workflows.
The monodomain model is widely used in in-silico cardiology to describe excitation propagation in the myocardium. Frequently, operator splitting is used to decouple the stiff reaction term and the diffusion term in the monodomain model so that they can be solved separately. Commonly, the diffusion term is solved implicitly with a large time step while the reaction term is solved by using an explicit method with adaptive time stepping. In this work, we propose a fully explicit method for the solution of the decoupled monodomain model. In contrast to semi-implicit methods, fully explicit methods present lower memory footprint and higher scalability. However, such methods are only conditionally stable. We overcome the conditional stability limitation by proposing a dual adaptive explicit method in which adaptive time integration is applied for the solution of both the reaction and diffusion terms. We perform a set of numerical examples where cardiac propagation is simulated under physiological and pathophysiological conditions. Results show that the proposed method presents preserved accuracy and improved computational efficiency as compared to standard operator splitting-based methods.
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A 2021 study studied Cardiac propagation simulation. Dual adaptive explicit method vs. Standard operator splitting-based methods was evaluated on Accuracy and computational efficiency. A dual adaptive explicit method for solving the decoupled monodomain model presented preserved accuracy and improved computational efficiency compared to standard operator splitting-based methods.
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