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Parameter identification in cardiac electrophysiology using Proper Orthogonal Decomposition method

Muriel Boulakia 1, 2 Jean-Frédéric Gerbeau 2
2 REO - Numerical simulation of biological flows
LJLL - Laboratoire Jacques-Louis Lions, Inria Paris-Rocquencourt, UPMC - Université Pierre et Marie Curie - Paris 6
Abstract : We consider the problem of estimating some parameters (like ionic models or parameters involved in the initial stimulation) of a model of electrocardiograms (ECG) from the data of the Einthoven leads. This problem can be viewed as a first attempt to identify or to locate a pathology. The direct model is based on the bidomain equations in the heart and a Poisson equation in the torso. To keep the computational time reasonable, the evaluation of the direct problem is approximated with a reduced order model based on Proper Orthogonal Decomposition (POD). The optimization problem is solved using a genetic algorithm. Numerical tests show that, with noisy synthetic data, the proposed procedure allows to recover ionic parameters and initial activation regions with a fair accuracy.
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Submitted on : Sunday, December 11, 2011 - 1:45:27 PM
Last modification on : Saturday, March 28, 2020 - 2:21:33 AM
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Muriel Boulakia, Jean-Frédéric Gerbeau. Parameter identification in cardiac electrophysiology using Proper Orthogonal Decomposition method. FIMH2011 : Sixth International Conference on Functional Imaging and Modeling of the Heart, May 2011, New York, United States. pp.315-322, ⟨10.1007/978-3-642-21028-0_40⟩. ⟨hal-00650606⟩



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