Title
Stimulus protocol determines the most computationally efficient preconditioner for the bidomain equations.
Abstract
The efficient solution of the bidomain equations is a fundamental tool in the field of cardiac electrophysiology. When choosing a finite element discretization of the coupled system, one has to deal with the solution of a large, highly sparse system of linear equations. The conjugate gradient algorithm, along with suitable preconditioning, is the natural choice in this scenario. In this study, we identify the optimal preconditioners with respect to both stimulus protocol and mesh geometry. The results are supported by a comprehensive study of the mesh-dependence properties of several preconditioning techniques found in the literature. Our results show that when only intracellular stimulus is considered, incomplete LU factorization remains a valid choice for current cardiac geometries. However, when extracellular shocks are delivered to tissue, preconditioners that take into account the structure of the system minimize execution time and ensure mesh-independent convergence.
Year
DOI
Venue
2010
10.1109/TBME.2010.2078817
IEEE transactions on bio-medical engineering
Keywords
Field
DocType
electrocardiography,cellular biophysics,algebraic multigrid technique,mesh-dependence property,cardiac electrophysiology,computational efficiency,mesh generation,whole heart geometries,current cardiac geometry,preconditioning,stimulus protocol,biological tissue,extracellular shocks,mesh-independent convergence,finite element analysis,finite element solution,intracellular stimulus,medical computing,biological tissues,bidomain equations,incomplete lu factorization,conjugate gradient algorithm,mesh geometry
Conjugate gradient method,Convergence (routing),Discretization,System of linear equations,Preconditioner,Computer science,Algorithm,Finite element method,Incomplete LU factorization,Mesh generation
Journal
Volume
Issue
ISSN
57
12
1558-2531
Citations 
PageRank 
References 
6
0.65
5
Authors
4
Name
Order
Citations
PageRank
Miguel O. Bernabeu160.65
Pras Pathmanathan211111.77
Joe Pitt-Francis312113.88
David A. Kay424431.51