Original Article

Non-auditory Effect of Noise Pollution and Its Risk on Human Brain Activity in Different Audio Frequency Using Electroencephalogram Complexity

Abstract

Background: Noise pollution is one of the most harmful ambiance disturbances. It may cause many deficits in ability and activity of persons in the urban and industrial areas. It also may cause many kinds of psychopathies. Therefore, it is very important to measure the risk of this pollution in different area.

Methods: This study was conducted in the Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences from June to September of 2015, in which, different frequencies of noise pollution were played for volunteers. 16-channel EEG signal was recorded synchronously, then by using fractal dimension and relative power of Beta sub-band of EEG, the complexity of EEG signals was measured.

Results: As the results, it is observed that the average complexity of brain activity is increased in the middle of audio frequency range and the complexity map of brain activity changes in different frequencies, which can show the effects of frequency changes on human brain activity.

Conclusion: The complexity of EEG is a good measure for ranking the annoyance and non-auditory risk of noise pollution on human brain activity.

 

Basner M, Babisch W, Davis A, Brink M, Clark C, Janssen S, Stansfeld S (2014). Auditory and non-auditory effects of noise on health. Lancet, 383:1325-1332.

Hughes RW, Jones DM (2003). Indispensable benefits and unavoidable costs of unattended sound for cognitive functioning. Noise Health, 6 (21):63-76.

Stansfeld S, Haines M, Brown B (2000). Noise and health in the urban environment. Rev Environ Health, 15:43-82.

Miedema H, Oudshoorn C (2001). Annoyance from transportation noise: relationships with exposure metrics DNL and DENL and their confidence intervals. Environ Health Perspect, 109 (4):409-16.

Muzet A (2007). Environmental noise, sleep and health. Sleep Medicine Reviews, 11(2):135-142.

Van Kempen E, Babisch W (2012). The quantitative relationship between road traffic noise and hypertension: a meta-analysis. J Hypertens, 30 (6):1075-86.

Sørensen M, Andersen ZJ, Nordsborg RB, Jensen SS, Lillelund KG, Beelen R, Schmidt EB, Tjonneland A, Overvad K, Raaschou-Nielsen O (2012). Road traffic noise and incident myocardial infarction: a prospective cohort study. PLoS One, 7 (6):e39283.

Stansfeld SA, Matheson MP (2003). Noise pollution: non-auditory effects on health. Br Med Bull, 68:243-57.

Akan Z, Körpinar MA, Tulgar M (2011). Effects of noise pollution over the blood serum immunoglobulins and auditory system on the VFM airport workers, Van, Turkey. Environ Monit Assess 177 (1-4):537-43.

Ranft U, Schikowski T, Sugiri D, Krutmann J, Krämer U (2009). Long-term exposure to traffic-related particulate matter impairs cognitive function in the elderly. Environ Res, 109 (8):1004-11.

Fritschi L, Brown L, Kim R, Schwela D, Kephalopolous S (2011). Burden of disease from environmental noise: Quantification of healthy years life lost in Europe, World Health Organisation, available from www.who.int/quantifying_ehimpacts/publications/e94888/en/.

Öhrström E, Skånberg A, Svensson H, Gidlöf-Gunnarsson A (2006). Effects of road traffic noise and the benefit of access to quietness. J Sound Vib, 295 (1-2):40-59.

Lusk SL, Gillespie B, Hagerty BM, Ziemba RA (2004). Acute effects of noise on blood pressure and heart rate. Arch Environ Health, 59 (8):392-9.

Evans GW (2006). Child development and the physical environment. Annu Rev Psychol, 57:423-51.

Laufs H, Krakow K, Sterzer P, Eger E, Beyerle A, Salek-Haddadi A, Kleinschmidt A (2003). Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest. Proc Natl Acad Sci USA, 100 (19):11053-8.

Allahverdy A, Nasrabadi AM, Mohammadi MR (2011). Detecting ADHD children using symbolic dynamic of nonlinear features of EEG. ICEE, pp. 1-4.

Coben R, Clarke AR, Hudspeth W, Barry RJ (2008). EEG power and coherence in autistic spectrum disorder. Clin Neurophysiol, 119 (5):1002-9.

Lee Y-J, Zhu Y-S, Xu Y-H, Shen M-F, Zhang H-X, Thakor N (2001). Detection of non-linearity in the EEG of schizophrenic patients. Clin Neurophysiol, 112 (7):1288-94.

Chambayil B, Singla R, Jha R (2010). Virtual keyboard BCI using Eye blinks in EEG. WiMob, pp. 466-70.

Aguilar JM, Castillo J, Elias D (2015). EEG Signals Processing Based on Fractal Dimension Features and Classified by Neural Network and Support Vector Machine in Motor Imagery for a BCI. IFMBE Procedings, 49: 615-8.

Woo J-S, Muller K-R, Lee S-W (2015). Classifying directions in continuous arm movement from EEG signals. Brain-Computer Interface (BCI), 2015 3rd International Winter Conference on IEEE, pp. 1-2.

Sharif B, Jafari AH (2015). A new approach to automatically generate optimal Poincaré plane from discrete time series, Electrical and Computer Engineering (CCECE), 2015 IEEE 28th Canadian Conference on, IEEE, pp. 581-6.

Akar SA, Kara S, Latifoğlu F, Bilgiç V (2015). Investigation of the noise effect on fractal dimension of EEG in schizophrenia patients using wavelet and SSA-based approaches. Biomed Signal Process Control, 18:42-8.

Klem GH, Lüders HO, Jasper H, Elger C (1999). The ten-twenty electrode system of the International Federation. Electroencephalogr Clin Neurophysiol Suppl, 52:3-6.

Esteller R, Vachtsevanos G, Echauz J, Litt B (2001). A comparison of waveform fractal dimension algorithms. IEEE Trans Circuits Syst I, 48 (2):177-83.

Sandau K, Kurz H (1997). Measuring fractal dimension and complexity—an alternative approach with an application. J Microsc, 186 (2):164-176.

Katz MJ (1988). Fractals and the analysis of waveforms. Comput Biol Med, 18 (3):145-56.

Sevcik C (2010). A procedure to estimate the fractal dimension of waveforms. Chaos Soliton Fractals,1003.5266.

Adeli H, Ghosh-Dastidar S, Dadmehr N (2007). A wavelet-chaos methodology for analysis of EEGs and EEG subbands to detect seizure and epilepsy. IEEE Trans Biomed Eng, 54(2):205-11.

Persson Waye K, Bengtsson J, Kjellberg A, Benton S (2001) , Low frequency noise "pollution" interferes with perfor-mance. Noise Health, 4 (13): 33-49.

Regecová V, Kellerová E (1995). Effects of urban noise pollution on blood pressure and heart rate in preschool children. J Hypertens, 13 (4): 405-12.

Files
IssueVol 45 No 10 (2016) QRcode
SectionOriginal Article(s)
Keywords
Noise pollution Brain activity EEG Fractal dimension Complexity

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
1.
ALLAHVERDY A, JAFARI AH. Non-auditory Effect of Noise Pollution and Its Risk on Human Brain Activity in Different Audio Frequency Using Electroencephalogram Complexity. Iran J Public Health. 2016;45(10):1332-1339.