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Analysis of the Effects of High-Voltage Transmission Line on Human Stress and Attention Through Electroencephalography (EEG)

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Abstract

Knowing the variable-frequency, high-intensity electromagnetic field plays an important role in the humans’ surroundings, numerous studies have been carried out on stress and attention based on EEG data. In this study, a comparison was drawn between the brain waves of individuals living near high-voltage transmission towers and those of people living outside of these zones. The levels of stress and attention were also assessed based on the brain activity of the participants. First, a general questionnaire is completed by the volunteers, and the predisposed samples are included in the research following the screening process. Two 10-member groups (average age of 27 years) of adult males were selected for the research. In one of the groups, the participants are not exposed to high-voltage electric fields. The homes of the members of the second group are located beneath or near high-voltage transmission towers (at a maximum distance of 20 m). Using a 14-channel EEG system, the brain waves of each participant were recorded 5 times over 2 days in the eyes-open resting state while the participants were looking at a white screen. (Ten records of data were obtained per person.) The saliva samples of each participant were also obtained to assess the basal cortisol hormone. The mean EEG stress and attention indices were obtained based on the data on each person, and the mean cortisol level of each group was compared to that of the other group. The investigation and comparison results proved that the mean EEG attention indices of people exposed to high-voltage electric fields were lower than those of the ordinary people. On the other hand, the mean levels of basal EEG stress and salivary cortisol hormone were higher in the people exposed to high-voltage electric fields than the ordinary people. Given the variations of the mean indices of stress and attention in the EEGs and salivary samples of the participants as a result, self-efficacy decreases over time.

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References

  • Alimardani F, Boostani R (2018) DB-FFR: a modified feature selection algorithm to improve discrimination rate between bipolar mood disorder (BMD) and schizophrenic patients. Iran J Sci Technol Trans Electr Eng 42(3):251–260

    Article  Google Scholar 

  • Aliyari H et al (2015) The effects of fifa 2015 computer games on changes in cognitive, Hormonal and brain waves functions of young men volunteers. Basic Clin Neurosci 6(3):193

    MathSciNet  Google Scholar 

  • Aliyari H et al. (2018a) Effect of proximity to high-voltage fields: results of the neural network model and experimental model with macaques. Int J Environ Sci Technol. https://doi.org/10.1007/s13762-018-1830-8

    Article  Google Scholar 

  • Aliyari H et al (2018b) The beneficial or harmful effects of computer game stress on cognitive functions of players. Basic Clin Neurosci 9(3):177–186

    Article  Google Scholar 

  • Badcock NA et al (2013) Validation of the Emotiv EPOC® EEG gaming system for measuring research quality auditory ERPs. PeerJ 1:e38

    Article  Google Scholar 

  • Badcock NA et al (2015) Validation of the Emotiv EPOC EEG system for research quality auditory event-related potentials in children. PeerJ 3:e907

    Article  Google Scholar 

  • Blackhart GC, Minnix JA, Kline JP (2006) Can EEG asymmetry patterns predict future development of anxiety and depression? A preliminary study. Biol Psychol 72(1):46–50

    Article  Google Scholar 

  • Blankertz B et al (2008) Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Process Mag 25(1):41–56

    Article  Google Scholar 

  • Brady TF, Konkle T, Alvarez GA (2011) A review of visual memory capacity: beyond individual items and toward structured representations. J Vis 11(5):4

    Article  Google Scholar 

  • Cardinal RN et al (2002) Emotion and motivation: the role of the amygdala, ventral striatum, and prefrontal cortex. Neurosci Biobehav Rev 26(3):321–352

    Article  MathSciNet  Google Scholar 

  • Dedovic K et al (2009) The brain and the stress axis: the neural correlates of cortisol regulation in response to stress. Neuroimage 47(3):864–871

    Article  Google Scholar 

  • Delorme A, Makeig S (2004) EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134(1):9–21

    Article  Google Scholar 

  • Emanuel AE (2004) Summary of IEEE standard 1459: definitions for the measurement of electric power quantities under sinusoidal, nonsinusoidal, balanced, or unbalanced conditions. IEEE Trans Ind Appl 40(3):869–876

    Article  Google Scholar 

  • Ferreira HC et al (2010) Power line communication. Wiley Online Library, New York

    Book  Google Scholar 

  • Fuster JM (1988) Prefrontal cortex, in comparative neuroscience and neurobiology. Springer, Berlin, pp 107–109

    Book  Google Scholar 

  • Gamberale F et al (1989) Acute effects of ELF electromagnetic fields: a field study of linesmen working with 400 kV power lines. Occup Environ Med 46(10):729–737

    Article  Google Scholar 

  • Guyon I, Elisseeff A (2006) An introduction to feature extraction. In: Guyon I, Nikravesh M, Gunn S, Zadeh LA (eds) Feature Extraction. Studies in Fuzziness and Soft Computing, vol 207. Springer, Berlin, Heidelberg, pp 1–25

    Chapter  Google Scholar 

  • Ijjada MS et al. (2015) Evaluation of wearable head set devices in older adult populations for research. In: 2015 international conference on computational science and computational intelligence (CSCI), 2015. IEEE

  • Ivancsits S et al (2005) Cell type-specific genotoxic effects of intermittent extremely low-frequency electromagnetic fields. Mutat Res, Genet Toxicol Environ Mutagen 583(2):184–188

    Article  Google Scholar 

  • Kazemi M et al (2018) Effects of the extremely low frequency electromagnetic fields on NMDA-receptor gene expression and visual working memory in male rhesus macaques. Basic Clin Neurosci 9(3):167–176

    Article  MathSciNet  Google Scholar 

  • Kevric J, Subasi A (2017) Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system. Biomed Signal Process Control 31:398–406

    Article  Google Scholar 

  • Laakso M et al (1995) Volumes of hippocampus, amygdala and frontal lobes in the MRI-based diagnosis of early Alzheimer’s disease: correlation with memory functions. J Neural Transm Parkinson’s Dis Dement Sect 9(1):73–86

    Article  Google Scholar 

  • Lang M (2012) Investigating the Emotiv EPOC for cognitive control in limited training time. Honours report, University of Canterbury, p 8

  • Lehrer P (2007) Principles and practice of stress management: advances in the field. Assoc Appl Psychophysiol Biofeedback 35(3):82–84

    Google Scholar 

  • Leroy A et al (2018) EEG dynamics and neural generators in implicit navigational image processing in adults with ADHD. Neuroscience 373:92–105

    Article  Google Scholar 

  • Levallois P et al (2001) Effects of electric and magnetic fields from high-power lines on female urinary excretion of 6-sulfatoxymelatonin. Am J Epidemiol 154(7):601–609

    Article  Google Scholar 

  • Lewis RS, Weekes NY, Wang TH (2007) The effect of a naturalistic stressor on frontal EEG asymmetry, stress, and health. Biol Psychol 75(3):239–247

    Article  Google Scholar 

  • Lupien SJ, Lepage M (2001) Stress, memory, and the hippocampus: can’t live with it, can’t live without it. Behav Brain Res 127(1):137–158

    Article  Google Scholar 

  • Lupien SJ et al (2005) Stress hormones and human memory function across the lifespan. Psychoneuroendocrinology 30(3):225–242

    Article  Google Scholar 

  • Majumder A (2004) Power line communications. IEEE Potentials 23(4):4–8

    Article  Google Scholar 

  • McEwen BS, Morrison JH (2013) The brain on stress: vulnerability and plasticity of the prefrontal cortex over the life course. Neuron 79(1):16–29

    Article  Google Scholar 

  • Moscovitch DA et al (2011) Frontal EEG asymmetry and symptom response to cognitive behavioral therapy in patients with social anxiety disorder. Biol Psychol 87(3):379–385

    Article  Google Scholar 

  • Oikonomou VP et al. (2017) A comparison study on EEG signal processing techniques using motor imagery EEG data. In: 2017 IEEE 30th international symposium on computer-based medical systems (CBMS), 2017. IEEE

  • Repacholi MH, Greenebaum B (1999) Interaction of static and extremely low frequency electric and magnetic fields with living systems: health effects and research needs. Bioelectromagnetics 20(3):133–160

    Article  Google Scholar 

  • Rodrak S, Wongsawat Y (2013) EEG brain mapping and brain connectivity index for subtypes classification of attention deficit hyperactivity disorder children during the eye-opened period. In: 2013 35th annual international conference of the IEEE engineering in medicine and biology society (EMBC), 2013. IEEE

  • Rommel A-S et al (2017) Altered EEG spectral power during rest and cognitive performance: a comparison of preterm-born adolescents to adolescents with ADHD. Eur Child Adolesc Psychiatry 26(12):1511–1522

    Article  Google Scholar 

  • Rowland N, Meile M, Nicolaidis S (1985) EEG alpha activity reflects attentional demands, and beta activity reflects emotional and cognitive processes. Science 228(4700):750–752

    Article  Google Scholar 

  • Salzman CD, Fusi S (2010) Emotion, cognition, and mental state representation in amygdala and prefrontal cortex. Annu Rev Neurosci 33:173–202

    Article  Google Scholar 

  • Sapolsky RM (2001) Depression, antidepressants, and the shrinking hippocampus. Proc Natl Acad Sci 98(22):12320–12322

    Article  Google Scholar 

  • Schmidt LA et al (2012) Test–retest reliability of regional electroencephalogram (EEG) and cardiovascular measures in social anxiety disorder (SAD). Int J Psychophysiol 84(1):65–73

    Article  Google Scholar 

  • Smeets T et al (2008) True or false? Memory is differentially affected by stress-induced cortisol elevations and sympathetic activity at consolidation and retrieval. Psychoneuroendocrinology 33(10):1378–1386

    Article  Google Scholar 

  • Squire LR (1992) Memory and the hippocampus: a synthesis from findings with rats, monkeys, and humans. Psychol Rev 99(2):195

    Article  Google Scholar 

  • Sroykham W, Wongsawat Y (2018) Estimation of testosterone/cortisol ratio by resting state EEG delta/beta ratio in elderly people. Neuroendocrinol Lett 39(1):75–82

    Google Scholar 

  • Tekieh E et al (2017) Role of basal stress hormones and amygdala dimensions in stress coping strategies of male rhesus monkeys in response to a hazard-reward conflict. Iran J Basic Med Sci 20(8):951–957

    Google Scholar 

  • Thibodeau R, Jorgensen RS, Kim S (2006) Depression, anxiety, and resting frontal EEG asymmetry: a meta-analytic review. American Psychological Association, Washington

    Google Scholar 

  • Wilson BW (1988) Chronic exposure to ELF fields may induce depression. Bioelectromagnetics 9(2):195–205

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

This research was conducted by financial support of Neuroscience Research Center, Baqiyatallah; Electrical Engineering Department of Amirkabir University of Technology (Tehran Polytechnic); Qazvin Branch, Islamic Azad University (Intelligent Systems and Cognitive Science Research Laboratory); and NeuroGame Research Laboratory.

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Correspondence to Hedayat Sahraei.

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Aliyari, H., Hosseinian, S.H., Menhaj, M.B. et al. Analysis of the Effects of High-Voltage Transmission Line on Human Stress and Attention Through Electroencephalography (EEG). Iran J Sci Technol Trans Electr Eng 43 (Suppl 1), 211–218 (2019). https://doi.org/10.1007/s40998-018-0151-8

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