3D space-dependent models for stochastic dosimetry applied to exposure to low frequency magnetic fields.
3D surrogate modeling
ELF-MF exposure
Kriging method
children exposure
stochastic dosimetry
Journal
Bioelectromagnetics
ISSN: 1521-186X
Titre abrégé: Bioelectromagnetics
Pays: United States
ID NLM: 8008281
Informations de publication
Date de publication:
Apr 2019
Apr 2019
Historique:
received:
03
05
2018
accepted:
21
02
2019
pubmed:
27
3
2019
medline:
20
7
2019
entrez:
27
3
2019
Statut:
ppublish
Résumé
In this study, an innovative approach that combines Principal Component Analysis (PCA) and Gaussian process regression (Kriging method), never used before in the assessment of human exposure to electromagnetic fields (EMF), was applied to build space-dependent surrogate models of the 3D spatial distribution of the electric field induced in central nervous system (CNS) of children of different ages exposed to uniform magnetic field at 50 Hz of 200 μT of amplitude with uncertain orientation. The 3D surrogate models showed very low normalized percentage mean square error (MSE) values, always lower than 0.16%, confirming the feasibility and accuracy of the approach in estimating the 3D spatial distribution of E with a low number of components. Results showed that the electric field values induced in CNS tissues of children were within the ICNIRP basic restrictions for general public, with 99th percentiles of the E values obtained for each orientation showing median values in the range 1.9-2.1 mV/m. Similar 3D spatial distributions of the electric fields were found to be induced in CNS tissues of children of different ages. Bioelectromagnetics. 9999:1-10, 2018. © 2019 Bioelectromagnetics Society.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
170-179Subventions
Organisme : French National Research Program for Environmental and Occupational Health of ANSES, Project ELFSTAT-In Depth Evaluation of Children's Exposure to ELF (40-800Hz) Magnetic Fields and Implications for Health Risk of New Technologies, 2015-2019
ID : 2015/1/202
Informations de copyright
© 2019 Bioelectromagnetics Society.