References of "Gaignaire, Roman"
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See detailStochastic Uncertainty Quantification of Eddy Currents in the Human Body by Polynomial Chaos Decomposition
Gaignaire, Roman ULg; Scorretti, Riccardo; V Sabariego, Ruth ULg et al

(2011)

The finite element method can be used to compute the electromagnetic fields induced into the human body by envi- ronmental extremely low frequency fields. However, the electric properties of tissues are ... [more ▼]

The finite element method can be used to compute the electromagnetic fields induced into the human body by envi- ronmental extremely low frequency fields. However, the electric properties of tissues are not precisely known and may vary depending on the individual, his/her age and other physiological parameters. We propose to account for some uncertainties on the conductivities of the brain tissues and to spread them out to the induced fields by means of a non-intrusive approach based on the chaos Hermite polynomial with the finite element method as a black box [3], [4]. [less ▲]

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See detailAn Amplitude Finite Element Formulation for Multiple-Scattering by a Collection of Convex Obstacles
Geuzaine, Christophe ULg; Vion, Alexandre ULg; Gaignaire, Roman ULg et al

in IEEE Transactions on Magnetics (2010), 46(8), 2963-2966

We present a multiple-scattering solver for nonconvex geometries obtained as the union of a finite number of convex obstacles. The algorithm is a finite element reformulation of a high-frequency integral ... [more ▼]

We present a multiple-scattering solver for nonconvex geometries obtained as the union of a finite number of convex obstacles. The algorithm is a finite element reformulation of a high-frequency integral equation technique proposed previously. It is based on an iterative solution of the scattering problem, where each iteration leads to the resolution of a single scattering problem in terms of a slowly oscillatory amplitude. [less ▲]

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See detailStochastic Uncertainty Quantification of the Conductivity in EEG Source Analysis by Using Polynomial Chaos Decomposition
Gaignaire, Roman ULg; Crevecoeur, Guillaume; Dupré, Luc et al

in IEEE Transactions on Magnetics (2010), 46(8), 3457-3460

The electroencephalogram (EEG) is one of the techniques used for the non-invasive diagnosis of patients suffering from epilepsy. EEG source localization identifies the neural activity, starting from ... [more ▼]

The electroencephalogram (EEG) is one of the techniques used for the non-invasive diagnosis of patients suffering from epilepsy. EEG source localization identifies the neural activity, starting from measured EEG. This numerical localization procedure has a resolution, which is difficult to determine due to uncertainties in the EEG forward models. More specifically, the conductivities of the brain and the skull in the head models are not precisely known. In this paper, we propose the use of a non-intrusive stochastic method based on a polynomial chaos decomposition for quantifying the possible errors introduced by the uncertain conductivities of the head tissues. The accuracy and computational advantages of this non-intrusive method for EEG source analysis is illustrated. Further, the method is validated by means of Monte Carlo simulations. [less ▲]

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