Particle Filter Tracking of Complex Stochastic Systems Applied to In Silico Wavefront Propagation

Abstract

A high dimensional tracking system based on the FithzHugh-Nagumo (FH-N) equations emulating the biological excitation and propagation dynamics of the action potential across cardiac cells is proposed. The modified FH-N model tracks the electric cardiac wavefronts on a tissue, emulating an approximated atrial fibrillation scenario. Bayesian tracking is achieved with two particle filter (PF) schemes: a sequential Auxiliary PF (APF) and a parallelized method, Independent APF (IAPF). The numerical results of the two examples, involving both estimation errors and running times, provide numerical evidence that support the theoretical findings.