• DocumentCode
    863350
  • Title

    Computational techniques for solving the bidomain equations in three dimensions

  • Author

    Vigmond, Edward J. ; Aguel, Felipe ; Trayanova, Natalia A.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada
  • Volume
    49
  • Issue
    11
  • fYear
    2002
  • Firstpage
    1260
  • Lastpage
    1269
  • Abstract
    The bidomain equations are the most complete description of cardiac electrical activity. Their numerical solution is, however, computationally demanding, especially in three dimensions, because of the fine temporal and spatial sampling required. This paper methodically examines computational performance when solving the bidomain equations. Several techniques to speed up this computation are examined in this paper. The first step was to recast the equations into a parabolic part and an elliptic part. The parabolic part was solved by either the finite-element method (FEM) or the interconnected cable model (ICCM). The elliptic equation was solved by FEM on a coarser grid than the parabolic problem and at a reduced frequency. The performance of iterative and direct linear equation system solvers was analyzed as well as the scalability and parallelizability of each method. Results indicate that the ICCM was twice as fast as the FEM for solving the parabolic problem, but when the total problem was considered, this resulted in only a 20% decrease in computation time. The elliptic problem could be solved on a coarser grid at one-quarter of the frequency at which the parabolic problem was solved and still maintain reasonable accuracy. Direct methods were faster than iterative methods by at least 50% when a good estimate of the extracellular potential was required. Parallelization over four processors was efficient only when the model comprised at least 500 000 nodes. Thus, it was possible to speed up solution of the bidomain equations by an order of magnitude with a slight decrease in accuracy.
  • Keywords
    Galerkin method; bioelectric potentials; biological tissues; biology computing; cardiology; elliptic equations; finite difference methods; iterative methods; matrix multiplication; medical computing; mesh generation; parabolic equations; physiological models; sparse matrices; 3D numerical solution; Galerkin formulation; bidomain equations; cardiac electrical activity; cardiac tissue; coarser grid; computational performance; direct linear equation system solvers; elliptic part; extracellular potential; extracellular potential fields; finite difference; finite-element method; grid generation; interconnected cable model; intracellular potential fields; iterative solvers; parabolic part; parallel computing; parallelizability; scalability; sparse matrix-vector multiplication; transmembrane current density; Biomedical engineering; Computational modeling; Equations; Extracellular; Finite element methods; Frequency; Heart; Iterative methods; Performance analysis; Sampling methods; Algorithms; Anisotropy; Computing Methodologies; Electric Conductivity; Electrophysiology; Finite Element Analysis; Heart; Heart Conduction System; Humans; Membrane Potentials; Models, Cardiovascular; Myocardium; Numerical Analysis, Computer-Assisted; Quality Control; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2002.804597
  • Filename
    1046934