Bayesian experiment planning applied to numerical dosimetry

To protect people from electromagnetic field, Basic Restrictions (BR) are defined [1]. These BR fix a limit to be not exceeded. The metric associated with these BR is the Specific Absorption Rate (SAR). Reference Levels (RL) are also defined since the BR are difficult to check in situ. These RL set the maximum allowed electromagnetic field. The compliance to RL guaranties the compliance to BR. To evaluate the SAR in the human body, some anatomical models (phantoms) and numerical methods are used (e.g. Finite Difference in Time Domain). Based on this, studies show that for some configurations the Whole Body SAR (WBSAR) is close to BR. Other studies stressed the variability of the WBSAR due to the variability of human morphology [2]. Despite the computing resources development, the number of the phantoms is very limited. This limited number of phantoms does not allow using usual method such as Monte Carlo to assess the maximal threshold of the WBSAR for a given population. Hence the construction of a model of the WBSAR as a function of morphology is required. Nevertheless, the WBSAR is impacted by the external morphology (height and weight) and the internal morphology (proportion of fat, proportion of muscles...). But there is no statistical data concerning the internal ones. In this paper, the external morphology is focused and the internal morphology is released by considering homogeneous phantoms. A Bayesian sequential experiment planning is proposed. This method consists in refining the region of interest of the WBSAR statistical distribution for a given population. This region of interest is the threshold of the WBSAR at 95% (WBSAR95). This study is conducted in the case of a plane wave vertically polarized and frontally oriented on phantoms. The incident power is equal to 1W/m². The frequency is fixed at 2.1GHz

Plan d'expériences séquentiel appliqué à la dosimétrie numérique

Dans ce papier nous allons proposer une méthodologie consistant à trouver la valeur du Débit d'Absorption Spécifique du Corps Entier (DAS_CE) qui couvre 95% d'une population donnée. Cette méthode repose d'une part sur de l'Inférence Bayesienne et d'autre part sur un modèle paramétrique de prédiction du DAS_CE en fonction de la morphologie ainsi que des outils de simulations numériques

A Novel Methodology to Evaluate Uplink Exposure by Personal Devices in Wireless Networks

International audienceOver the last 20 years, the wireless technology has known a large development in terms of devices and services, accompanied consequently by considerable doubts about the level of exposure to the electromagnetic fields radiated by these systems. An intermediate step in the assessment of the real exposure is to statistically model the input power delivered to these personal devices during an uplink transmission. In this spirit, we propose a systematic methodology for the characterization of the variability of the delivered input power for given propagation conditions. This methodology first addresses the influence of the personal devices relative positioning, with respect to the user's body on the antennas performance as well as on the exposure level. Second, it add-resses the sensitivity of the input power to the characteristics of the propagation channel. The exposure levels have been investigated from specific absorption rates computed using finite-difference time-domain simulations on a realistic numerical model of child bodies. The input power is directly related to the antenna radiation pattern and to the local propagation scenario, through effects such as body obstruction and multipath diversity. The statistical analysis shows that the delivered input power can be modeled by an inverse Gaussian or a log-normal distribution

Statistical Analysis of the Whole Body Absorption Depending on Anatomical Human Characteristics at the Frequency of 2.1 GHz

International audienceIn this paper we propose an identification of morphological factors that may impact the Whole Body Specific Absorption Rate (WBSAR). The study is conducted for the case of an exposure to a front plane wave at the 2100MHz frequency carrier. This study is based on the development of different regression models for estimating the WBSAR as a function of morphological factors morphology. For this manner, a database of twelve anatomical human models (phantoms) has been considered. Also, eighteen supplementary phantoms obtained using morphing technique were generated to build the requested relation. The paper presents three models based on external morphological factors like the Body Surface Area (BSA), the Body Mass Index (BMI) or the body mass. These models show good results for families obtained by morphing technique on the estimation of the WBSAR (< 10%) but still less accurate (30%) when applied for different original phantoms. This study stresses the importance of the internal morphological factors such as muscle and fat proportions in the characterization of the WBSAR. The regression models are then improved using internal morphological factors with an estimation error around 10% on the WBSAR. Finally, this study is suited for establishing the statistical distribution of the WBSAR for a given population characterized by its morphology

Multidimensional collocation stochastic method to evaluate the Whole Specific Absorption Rate for a given population

To protect people from Electromagnetic Fields (EMF), ICNIRP has defined limits [1]. The Basic Restrictions (BR) set the maximum values of Specific Absorption Rate (SAR). Since BR are complex to assess ICNIRP has also derived the reference levels (RL) from BR. These RL were established to guaranty the compliance to BR. Several studies with human model (phantoms) show that even below the RL, the WBSAR (Whole Body averaged SAR) may exceed the BR due to the variability of human morphology [2]. The number of phantoms is very limited. Hence, t e characterization of the WBSAR for a given using usual methods such as Monte Carlo is not possible. To bridge this lack of phantoms a model for the WBSAR as a function of morphology is suitable. However, this model requires knowledge on internal morphology (proportion of fat, muscle...) and external ones (mainly height and weight) [5]. Due to the absence of statistical data concerning the internal morphology, the statistical distribution of the WBSAR is difficult to obtain. In this paper, the internal morphology is released by considering one equivalent tissue for the whole body. The stochastic collocation is used to characterize the distribution of the WBSAR for a given population. The study is conducted in the case of a plane wave operating at 2.1 GHz, vertically polarized and frontally oriented on phantoms. The incident power is equal to 1W/m²

Advanced human RF exposure assessment using FDTD and polynomial chaos expansion

International audienc