Abstract
Microscopic structural features of cardiac tissue play a fundamental role in determining complex spatio-temporal excitation dynamics at the macroscopic level. Recent efforts have been devoted to the development of mathematical models accounting for non-local spatio-temporal coupling able to capture these complex dynamics without the need of resolving tissue heterogeneities down to the micro-scale. In this work, we analyse in detail several important aspects affecting the overall predictive power of these modelling tools and provide some guidelines for an effective use of space-fractional models of cardiac electrophysiology in practical applications. Through an extensive computational study in simplified computational domains, we highlight the robustness of models belonging to different categories, i.e., physiological and phenomenological descriptions, against the introduction of non-locality, and lay down the foundations for future research and model validation against experimental data. A modern genetic algorithm framework is used to investigate proper parameterisations of the considered models, and the crucial role played by the boundary assumptions in the considered settings is discussed. Several numerical results are provided to support our claims.
Original language | English |
---|---|
Article number | 105152 |
Number of pages | 22 |
Journal | Communications in Nonlinear Science and Numerical Simulation |
Volume | 84 |
DOIs | |
Publication status | Published - May 2020 |
Fields of science
- 101 Mathematics
- 101013 Mathematical logic
- 101024 Probability theory
- 102001 Artificial intelligence
- 102003 Image processing
- 102019 Machine learning
- 102035 Data science
- 603109 Logic
- 202027 Mechatronics
JKU Focus areas
- Digital Transformation