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International Conference on Functional Imaging and Modeling of the Heart

FIMH 2011: Functional Imaging and Modeling of the Heart pp 315–322Cite as

Parameter Identification in Cardiac Electrophysiology Using Proper Orthogonal Decomposition Method

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6666))

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 and. 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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References

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Author information

Authors and Affiliations

  1. Université Pierre et Marie Curie-Paris 6, LJLL, Paris, F-75005, France

    M. Boulakia

  2. INRIA Paris-Rocquencourt, BP 105, F–78153, Le Chesnay Cedex, France

    J-F. Gerbeau

Authors
  1. M. Boulakia
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  2. J-F. Gerbeau
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Editor information

Editors and Affiliations

  1. Rutgers University, 08854, Piscataway, NJ, USA

    Dimitris N. Metaxas

  2. Department of Radiology, New York University, 560 First Avenue, 10016, New York, NY, USA

    Leon Axel

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© 2011 Springer-Verlag Berlin Heidelberg

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Boulakia, M., Gerbeau, JF. (2011). Parameter Identification in Cardiac Electrophysiology Using Proper Orthogonal Decomposition Method. In: Metaxas, D.N., Axel, L. (eds) Functional Imaging and Modeling of the Heart. FIMH 2011. Lecture Notes in Computer Science, vol 6666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21028-0_40

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  • DOI: https://doi.org/10.1007/978-3-642-21028-0_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21027-3

  • Online ISBN: 978-3-642-21028-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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