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

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URI: https://hdl.handle.net/10016/34823
ISSN: 2325-8861 Print on Demand (PoD)
ISSN: 2325-887X (online)
ISBN: 978-1-7281-0924-4 Print on Demand (PoD)
ISBN: 978-1-7281-0958-9 (online)
DOI: https://doi.org/10.22489/CinC.2018.233
UXXI: CC/0000033339
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particle_CinC_2018_ps.pdf (2.34 MB)
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2019-06-24
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IEEE
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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.
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Proceeding of 2018 Computing in Cardiology Conference (CinC), September 23-26, 2018, Maastricht, The Netherlands
Keywords
Mathematical model, Action potentials, Computational modeling, Bayes methods, Adaptation models, Markov processes
Bibliographic citation
2018 Computing in Cardiology Conference (CinC 2018), Maastricht, Netherlands, 23-26 September, 2018, v.45. Estados Unidos: IEEE.
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