IEEE Transactions on Biomedical Engineering · 2006 · 93 citations · 21 references
Natural SciencesBiophysicsMathematicsComputational BiophysicsComputational PhysicsDifferential EquationsNonlinear DynamicsNumerical AlgorithmsNumerical AnalysisNumerical Methods For Differential EquationsNumerical StabilitySystems Of Differential EquationsDifferential Equation SolversMonodomain ModelsNonlinear Dynamical SystemsNonlinear SystemsNumerical Solutions Of Ordinary Differential EquationsNumerical Stability AnalysisOrdinary Differential Equation SolversStability Of Numerical Schemes
Most numerical schemes for solving the monodomain or bidomain equations use a forward approximation to some or all of the time derivatives. This approach, however, constrains the maximum timestep that may be used by stability considerations as well as accuracy considerations. Stability may be ensured by using a backward approximation to all time derivatives, although this approach requires the solution of a very large system of nonlinear equations at each timestep which is computationally prohibitive. In this paper we propose a semi-implicit algorithm that ensures stability. A linear system is solved on each timestep to update the transmembrane potential and, if the bidomain equations are being used, the extracellular potential. The remainder of the equations to be solved uncouple into small systems of ordinary differential equations. The backward Euler method may be used to solve these systems and guarantee numerical stability: as these systems are small, only the solution of small nonlinear systems are required. Simulations are carried out to show that the use of this algorithm allows much larger timesteps to be used with only a minimal loss of accuracy. As a result of using these longer timesteps the computation time may be reduced substantially.
21
Choice Reviews Online · 2008 · 2.8K citations
Robert I. McLachlan, G. Quispel · Acta Numerica · 2002 · 661 citations