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

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

Author(s): Ríos Muñoz, Gonzalo Ricardo; Artés Rodríguez, Antonio; Míguez Arenas, Joaquín
Publisher: IEEE
Issued date: 2019-06-24
Citation: 2018 Computing in Cardiology Conference (CinC 2018), Maastricht, Netherlands, 23-26 September, 2018, v.45. Estados Unidos: IEEE.
ISBN: 978-1-7281-0924-4 Print on Demand (PoD)
978-1-7281-0958-9 (online)
ISSN: 2325-8861 Print on Demand (PoD)
2325-887X (online)
DOI: https://doi.org/10.22489/CinC.2018.233
xmlui.dri2xhtml.METS-1.0.item-contributor-funder: Comunidad de Madrid
Ministerio de Economía y Competitividad (España)
Sponsor: This work has been partly supported by MINECO/FEDER (ADVENTURE, id. TEC2015-69868-C2-1-R), and Comunidad de Madrid (project CASI-CAM-CM, id. S2013/ICE-2845).
Project: Gobierno de España. TEC2015-69868-C2-1-R/ADVENTURE
Comunidad de Madrid. S2013/ICE-2845
Keywords: Mathematical model , Action potentials , Computational modeling , Bayes methods , Adaptation models , Markov processes
URI: http://hdl.handle.net/10016/34823
Rights: © 2018, IEEE

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 wavefro [+]

Description:

Proceeding of 2018 Computing in Cardiology Conference (CinC), September 23-26, 2018, Maastricht, The Netherlands

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