Stochastic modelling of 3D electric field in children brain exposed to 50 Hz magnetic field

This study focused on the evaluation of the electric field induced in the brain grey matter of a 5 years child when exposed to uniform magnetic field at 50 Hz with uncertain orientation. An innovative approach that combines Principal Component Analysis (PCA) and Gaussian process regression (Kriging method) in order to build space-dependent surrogate models was applied and validated. Preliminary results showed the feasibility of the approach.

Mots clés

stochastic dosimetry ELF-MF exposure surrogate modelling

Domaines

Santé publique et épidémiologie Machine Learning [stat.ML] Applications [stat.AP] Modélisation et simulation Statistiques [math.ST]

Fichier principal

GNB_2018_Chiaramello.pdf (694.59 Ko)

Origine	Fichiers produits par l'(les) auteur(s)

Laurent Le Brusquet : Connectez-vous pour contacter le contributeur

https://centralesupelec.hal.science/hal-01871375

Soumis le : lundi 10 septembre 2018-16:44:08

Dernière modification le : lundi 18 mars 2024-03:05:34

Archivage à long terme le : mardi 11 décembre 2018-15:55:33

Dates et versions

hal-01871375 , version 1 (10-09-2018)

Identifiants

HAL Id : hal-01871375 , version 1

Citer

Emma Chiaramello, Marta Parazzini, Serena Fiocchi, Marta Bonato, Laurent Le Brusquet, et al.. Stochastic modelling of 3D electric field in children brain exposed to 50 Hz magnetic field. Sixth National Congress of Bioenginnering, Jun 2018, Milan, Italy. ⟨hal-01871375⟩

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CNRS SUP_LSS SUP_SIGNAUX CENTRALESUPELEC TDS-MACS UNIV-PARIS-SACLAY GS-ENGINEERING GS-COMPUTER-SCIENCE

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