Literature DB >> 19380319

Numerical solution of the bidomain equations.

S Linge1, J Sundnes, M Hanslien, G T Lines, A Tveito.   

Abstract

Knowledge of cardiac electrophysiology is efficiently formulated in terms of mathematical models. However, most of these models are very complex and thus defeat direct mathematical reasoning founded on classical and analytical considerations. This is particularly so for the celebrated bidomain model that was developed almost 40 years ago for the concurrent analysis of extra- and intracellular electrical activity. Numerical simulations based on this model represent an indispensable tool for studying electrophysiology. However, complex mathematical models, steep gradients in the solutions and complicated geometries lead to extremely challenging computational problems. The greatest achievement in scientific computing over the past 50 years has been to enable the solving of linear systems of algebraic equations that arise from discretizations of partial differential equations in an optimal manner, i.e. such that the central processing unit (CPU) effort increases linearly with the number of computational nodes. Over the past decade, such optimal methods have been introduced in the simulation of electrophysiology. This development, together with the development of affordable parallel computers, has enabled the solution of the bidomain model combined with accurate cellular models, on geometries resembling a human heart. However, in spite of recent progress, the full potential of modern computational methods has yet to be exploited for the solution of the bidomain model. This paper reviews the development of numerical methods for solving the bidomain model. However, the field is huge and we thus restrict our focus to developments that have been made since the year 2000.

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Year:  2009        PMID: 19380319     DOI: 10.1098/rsta.2008.0306

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  6 in total

1.  Increased interstitial loading reduces the effect of microstructural variations in cardiac tissue.

Authors:  Marjorie Letitia Hubbard; Craig S Henriquez
Journal:  Am J Physiol Heart Circ Physiol       Date:  2010-01-22       Impact factor: 4.733

2.  Electromechanical feedback with reduced cellular connectivity alters electrical activity in an infarct injured left ventricle: a finite element model study.

Authors:  Samuel T Wall; Julius M Guccione; Mark B Ratcliffe; Joakim S Sundnes
Journal:  Am J Physiol Heart Circ Physiol       Date:  2011-11-04       Impact factor: 4.733

3.  Program Code Generator for Cardiac Electrophysiology Simulation with Automatic PDE Boundary Condition Handling.

Authors:  Florencio Rusty Punzalan; Yoshitoshi Kunieda; Akira Amano
Journal:  PLoS One       Date:  2015-09-10       Impact factor: 3.240

4.  Adaptive Mesh Refinement and Adaptive Time Integration for Electrical Wave Propagation on the Purkinje System.

Authors:  Wenjun Ying; Craig S Henriquez
Journal:  Biomed Res Int       Date:  2015-10-25       Impact factor: 3.411

Review 5.  In silico models for evaluating proarrhythmic risk of drugs.

Authors:  Minki Hwang; Chul-Hyun Lim; Chae Hun Leem; Eun Bo Shim
Journal:  APL Bioeng       Date:  2020-06-04

6.  Deriving the Bidomain Model of Cardiac Electrophysiology From a Cell-Based Model; Properties and Comparisons.

Authors:  Karoline Horgmo Jæger; Aslak Tveito
Journal:  Front Physiol       Date:  2022-01-07       Impact factor: 4.566

  6 in total

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