A Multilayer Perceptron Neural Network–Based Model for Predicting Subjective Health Symptoms in People Living in the Vicinity of Mobile Phone Base Stations

H. Parsaei, M. Faraz, and S. M. J. Mortazavi. Ecopsychology. Jun 2017.99-105. http://doi.org/10.1089/eco.2017.0011

Advances in modern technologies such as telecommunication have widely expanded the applications of wireless systems. Therefore, humans are continuously exposed to electromagnetic fields (EMFs)produced by widely used devices such as mobile and cordless phones and Wi-Fi routers. According to the World Health Organization, electromagnetic hypersensitivity (EHS) is the medical term for a variety of nonspecific symptoms that afflicted subjects attribute to exposure to different sources of EMFs. About 25% of the general population reports different levels of environmental intolerance to factors such as EMFs, and studies performed in Europe show that about 75% of general practitioners had visited patients complaining of EHS. In this paper, multilayer perceptron neural network (MLPNN)–based models are proposed to predict the subjective health symptoms in inhabitants living in the vicinity of mobile phone base stations. The classifier uses several parameters such as demographic data, environmental exposure to a mobile phone station, and the health conditions of an individual as input to estimate subjective health symptoms. Out of 699 data sets recorded from 363 men and 336 women via questionnaire, 70% were used for training, 15% for validation, and the remaining 15% for testing the developed system. The performance of the developed system (sensitivity and specificity) in predicting the subjective health symptoms is as follows: headache (72%, 91%), fatigue (8%, 98%), sleep disturbance (97%, 93%), dizziness (65%, 85%), vertigo (65%, 84%). These promising results suggest that this system might be useful as a means for predicting the health symptoms in people living in the vicinity of mobile phone base stations, which ultimately enhances the quality of life of these individuals through providing appropriate medical care and introducing effective methods for reducing the effect of these exposures.


pdf: Link:  eco.2017.0011

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