# name
Numerical Implementation of Representative Mobile Phone Models
                for Epidemiological Studies

# metadata.dc.description.abstract[].value
This paper describes an implementation method and the results of numerical mobile phone models representing real phone models that
have been released on the Korean market since 2002. The aim is to estimate the electromagnetic absorption in the human brain for casecontrol
studies to investigate health risks related to mobile phone use. Specific absorption rate (SAR) compliance test reports about
commercial phone models were collected and classified in terms of elements such as the external body shape, the antenna, and the
frequency band. The design criteria of a numerical phone model representing each type of phone group are as follows. The outer dimensions
of the phone body are equal to the average dimensions of all commercial models with the same shape. The distance and direction of
the maximum SAR from the earpiece and the area above –3 dB of the maximum SAR are fitted to achieve the average obtained by
measuring the SAR distributions of the corresponding commercial models in a flat phantom. Spatial peak 1-g SAR values in the cheek
and tilt positions against the specific anthropomorphic mannequin phantom agree with average data on all of the same type of
commercial models. Second criterion was applied to only a few types of models because not many commercial models were available. The
results show that, with the exception of one model, the implemented numerical phone models meet criteria within 30%.

# metadata.dc.publisher[].value
The Korean Institute of Electromagnetic Engineering and Science

# metadata.dc.relation.ispartof[].value
Journal of Electromagnetic Engineering and Science, 2016, vol.
                16, num. 2, p. 87-99

# metadata.dc.rights[].value
cc by (c) The Korean Institute of Electromagnetic Engineering and Science, 2016

# metadata.dc.source[].value
Articles publicats en revistes (ISGlobal)

# metadata.dc.title[].value
Numerical Implementation of Representative Mobile Phone Models
                for Epidemiological Studies