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Section: Partnerships and Cooperations
International Initiatives
Inria International Labs
International Laboratory for Research in Computer Science and Applied Mathematics
Associate Team involved in the International Lab:
EPICARD
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International Partner (Institution - Laboratory - Researcher):
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See also: https://team.inria.fr/carmen/epicard/
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Model personalization is a very challenging question in the numerical modeling community, especially for medical applications like cardiac electrophysiology. Our main idea is to adapt the input data like model parameters and boundary conditions of the electrophysiological measurements. There are two mathematical problems raising from this challenge. The first issue is the identifiability of the parameters and the sensitivity of the identification problem to the measured data. The question is: For given measurements, could we prove that there exist a set of parameters that allows to fit these measurements? The second issue is, how can we estimate parameters, when they are identifiable,? Our idea is to provide a theoretical analysis for the identification of each of the parameters and to construct suitable numerical methods to estimate them.
Inria International Partners
Informal International Partners
Y. Coudière works with the group of Prof. Y. Bourgault from the Department of Mathematics and Statistics of the University of Ottawa (Canada). Some results on the numerical analysis of time-stepping methods from C. Douanla's PhD were carried out together, as well as some theoretical results on parameter identification in the PhD of A. Gérard.
M. Potse works with the group of Prof. U. Schotten at Maastricht University (The Netherlands) and the Center for Computational Medicine in Cardiology at the Università della Svizzera italiana (Lugano, Switzerland) on simulation studies of atrial fibrillation [56]. The Maastricht group was partially funded by the FP7 project EUTRAF and our simulations were supported by GENCI (section 7.2.3).
N. Zemzemi works with Cesare Corrado at King's College London on the development of new eikonal models allowing conduction velocity adaptation [16].