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Stochastic Finite Element Method for torso conductivity uncertainties quantification in electrocardiography inverse problem

hal.structure.identifierLaboratoire d'Etudes et Recherche en Mathématiques Appliquées [LERMA]
dc.contributor.authorABOULAICH, Rajae
hal.structure.identifierLaboratoire d'Etudes et Recherche en Mathématiques Appliquées [LERMA]
dc.contributor.authorFIKAL, Najib
hal.structure.identifierModelization and Scientific Computing [Mohammadia Engineering School]
dc.contributor.authorEL GUARMAH, Emahdi
hal.structure.identifierModélisation et calculs pour l'électrophysiologie cardiaque [CARMEN]
dc.contributor.authorZEMZEMI, Nejib
dc.date.accessioned2024-04-04T03:15:04Z
dc.date.available2024-04-04T03:15:04Z
dc.date.issued2016
dc.identifier.issn0973-5348
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/194120
dc.description.abstractEnThe purpose of this paper is to study the influence of errors and uncertainties of the input data, like the conductivity, on the electrocardiography imaging (ECGI) solution. In order to do that, we propose a new stochastic optimal control formulation, permitting to calculate the distribution of the electric potentiel on the heart from the measurement on the body surface. The discretization is done using stochastic Galerkin method allowing to separate random and deterministic variables. Then, the problem is discretized, in spatial part, using the finite element method and the polynomial chaos expansion in the stochastic part of the problem. The considered problem is solved using a conjugate gradient method where the gradient of the cost function is computed with an adjoint technique. The efficiency of this approach to solve the inverse problem and the usability to quantify the effect of conductivity uncertainties in the torso are demonstrated through a number of numerical simulations on a 2D analytical geometry and on a 2D cross section of a real torso.
dc.language.isoen
dc.publisherEDP Sciences
dc.subject.enand phrases: electrocardiography forward problem
dc.subject.enelectrocardiography inverse problem
dc.subject.enstochastic finite elements
dc.subject.enchaos polynomial
dc.subject.enuncertainty quantification
dc.subject.enstochastic processes
dc.subject.enstochastic Galerkin method Mathematics Subject Classification: 35Q53
dc.subject.en34B20
dc.subject.en35G31
dc.title.enStochastic Finite Element Method for torso conductivity uncertainties quantification in electrocardiography inverse problem
dc.typeArticle de revue
dc.identifier.doi10.1051/mmnp/201611201
dc.subject.halInformatique [cs]/Modélisation et simulation
dc.subject.halMathématiques [math]/Equations aux dérivées partielles [math.AP]
dc.subject.halMathématiques [math]/Optimisation et contrôle [math.OC]
bordeaux.journalMathematical Modelling of Natural Phenomena
bordeaux.page1-19
bordeaux.volume11
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue2
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01289144
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01289144v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Mathematical%20Modelling%20of%20Natural%20Phenomena&rft.date=2016&rft.volume=11&rft.issue=2&rft.spage=1-19&rft.epage=1-19&rft.eissn=0973-5348&rft.issn=0973-5348&rft.au=ABOULAICH,%20Rajae&FIKAL,%20Najib&EL%20GUARMAH,%20Emahdi&ZEMZEMI,%20Nejib&rft.genre=article


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