Abstract

The interaction between biological tissue and electromagnetic fields (EMF) is a topic of increasing interest due to the rising prevalence of background EMF in the past decades. Previous studies have attempted to measure the effects of EMF on brainwaves using EEG recordings, but are typically hampered by experimental and environmental factors. In this study, we present a framework for measuring the impact of EMF on EEG while controlling for these factors. A Bayesian statistical approach is employed to provide robust statistical evidence of the observed EMF effects. This study included 32 healthy participants in a double-blinded crossover counterbalanced design. EEG recordings were taken from 63 electrodes across 6 brain regions. Participants underwent a measurement protocol comprising two 18-min sessions with alternating blocks of eyes open (EO) and eyes closed (EC) conditions. Group 1 (n = 16) had EMF during the first session and sham during the second session; group 2 (n = 16) had the opposite. Power spectral density plots were generated for all sessions and brain regions. The Bayesian analysis provided statistical evidence for the presence of an EMF effect in the alpha band power density in the EO condition. This measurement protocol holds potential for future research on the impact of novel transmission protocols.

Details

Title
Effects of mobile phone electromagnetic fields on brain waves in healthy volunteers
Author
van der Meer, Johan N. 1 ; Eisma, Yke B. 2 ; Meester, Ronald 3 ; Jacobs, Marc 1 ; Nederveen, Aart J. 1 

 Amsterdam UMC Location AMC, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands (GRID:grid.509540.d) (ISNI:0000 0004 6880 3010) 
 TU Delft, Cognitive Robotics, Faculty of Mechanical, Maritime and Materials Engineering (3mE), Delft, The Netherlands (GRID:grid.5292.c) (ISNI:0000 0001 2097 4740) 
 Vrije Universiteit, Department of Mathematics, Amsterdam, The Netherlands (GRID:grid.12380.38) (ISNI:0000 0004 1754 9227) 
Pages
21758
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2899562028
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.