Analysis of three-dimensional SAR distributions emitted by mobile phones in an epidemiological perspective

Isabelle Deltour*, Joe Wiart, Masao Taki, Kanako Wake, Nadège Varsier, Simon Mann, Joachim Schüz, Elisabeth Cardis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

The three-dimensional distribution of the specific absorption rate of energy (SAR) in phantom models was analysed to detect clusters of mobile phones producing similar spatial deposition of energy in the head. The clusters' characteristics were described from the phones external features, frequency band and communication protocol. Compliance measurements with phones in cheek and tilt positions, and on the left and right side of a physical phantom were used. Phones used the Personal Digital Cellular (PDC), Code division multiple access One (CdmaOne), Global System for Mobile Communications (GSM) and Nordic Mobile Telephony (NMT) communication systems, in the 800, 900, 1500 and 1800MHz bands. Each phone's measurements were summarised by the half-ellipsoid in which the SAR values were above half the maximum value. Cluster analysis used the Partitioning Around Medoids algorithm. The dissimilarity measure was based on the overlap of the ellipsoids, and the Manhattan distance was used for robustness analysis. Within the 800MHz frequency band, and in part within the 900MHz and the 1800MHz frequency bands, weak clustering was obtained for the handset shape (bar phone, flip with top and flip with central antennas), but only in specific positions (tilt or cheek). On measurements of 120 phones, the three-dimensional distribution of SAR in phantom models did not appear to be related to particular external phone characteristics or measurement characteristics, which could be used for refining the assessment of exposure to radiofrequency energy within the brain in epidemiological studies such as the Interphone.

Original languageEnglish
Pages (from-to)634-643
Number of pages10
JournalBioelectromagnetics
Volume32
Issue number8
DOIs
Publication statusPublished - Dec 2011

Keywords

  • Brain
  • Cluster
  • Electromagnetic fields
  • Radiofrequency fields

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