The electromagnetic-thermal dosimetry for the homogeneous human brain model

The electromagnetic-thermal dosimetry model of the human brain exposed to electromagnetic (EM) radiation is developed. The EM model based on the surface integral equation (SIE) formulation is derived using the equivalence theorem for the case of a lossy homogeneous dielectric body. The thermal dosim...

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Bibliographic Details
Published in:Engineering analysis with boundary elements 2016-02, Vol.63, p.61-73
Main Authors: Cvetković, Mario, Poljak, Dragan, Hirata, Akimasa
Format: Article
Language:English
Subjects:
Brain
Dosimeters
Dosimetry
Electromagnetic model
Exposure
Homogeneous human brain model
Human
Mathematical analysis
Mathematical models
Parameter sensitivity analysis
Surface integral equation approach
Temperature distribution
Temperature prediction
Thermal dosimetry model
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Summary:The electromagnetic-thermal dosimetry model of the human brain exposed to electromagnetic (EM) radiation is developed. The EM model based on the surface integral equation (SIE) formulation is derived using the equivalence theorem for the case of a lossy homogeneous dielectric body. The thermal dosimetry model of the brain is based on the form of Pennes׳ equation for heat transfer in biological tissue. The numerical solution of the EM model is carried out using the Method of Moments (MoM) while the bioheat equation is solved using the finite element method (FEM). Developed EM-thermal model has been applied for the internal dosimetry of the human brain to assess the absorbed EM energy and the consequent temperature rise due to the exposure of 900MHz plane wave. Due to the variability of various parameters, the sensitivity of the maximum, minimum and the average steady-state temperature, on the various thermal parameters have been examined, as well as the influence of the parameters variation on the temperature distribution in case of EM exposure. The proposed model may be found useful in the rapid assessment of the temperature distribution in the human brain, prior to having to deal with a tedious development of a more complex models.
ISSN:0955-7997
1873-197X
DOI:10.1016/j.enganabound.2015.11.002