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Investigation of Relationship between Noise Annoyance and Neurophysiological Responses of Drivers in Exposure to Tractor Sound
Majid Lashgari, Mohammadreza Arab,
Volume 6, Issue 3 ( Iranian Journal of Ergonomics 2018)
Abstract
Background & Objectives: Sound as a detrimental factor in working environments can create annoying conditions for people in addition to physical problems. Therefore, in addition to evaluating quantitative parameters such as pressure levels, it is absolutely necessary to study the quality parameters of the sound in the work environment. 
Methods: In this descriptive-analytic research, the sound of 285 MF tractor was recorded. Then, the EEG of five drivers were recorded in the pre-driving state and then when driving with the tractor in four different engine speed. The psychoacoustic annoyance model was used to assess the annoyance of tractor drivers. Then means were compared with Duncan comparison test at 5% probability level and the correlation between psychoacoustic acoustic and alpha and beta bands was determined.
Results: The results of ANOVA showed that different levels of engine speed on psychoacoustic annoyance were significant at 1% probability level. The results also showed a decrease in the amplitude of the alpha band, as well as an increase in the beta band amplitude due to increased engine speed. Regression results showed that there is a high correlation between the two alpha and beta bands and the psychoacoustic annoyance, so that the detection coefficient was 0.966 and 0.998, respectively, for the two bands alpha and beta. 
Conclusion: This study showed that changes in the quality parameters of the sound and consequently the resulting annoyance caused the amplitude changes in both the alpha and beta bands. So, it can be concluded that the psychoacoustic annoyance is a good indicator of brain activity.
 

Correlation Brain Signals and Tractor Sound Signals Based on Fractal Analysis
Majid Lashgari, Mohammadreza Arab, Mohsen Nadjafi, Ali Maleki,
Volume 9, Issue 2 (Iranian Journal of Ergonomics 2021)
Abstract
Background & Objectives: Due to the sound caused by various machines and tools in different agriculture sectors, occupational safety and health should be continuously evaluated. Indeed, the harmful effects of sound can be better reduced when the effects of sound on people's health and performance are fully known.
Methods: In this study, a garden tractor was used. Sixteen volunteers were exposed to the sound of the tractor, and their EEG was recorded at four different engine speeds. Then, Higuchi and Katz methods were used to calculate the fractal dimension of sound signals as well as brain signals.
Results: The results showed that by increasing engine speed, the values ​​of the fractal dimension in both Higuchi and Katz methods increased. The results also showed an increase in the fractal dimension of brain signals due to an increase in engine speed. The regression results also showed a high correlation between the two brain signals and the sound. The coefficient of explanation was 0.896 and 0.859 in Higuchi and Katz methods, respectively.
Conclusion: This study showed that people's reactions, when exposed to sound, can be predicted using the fractal dimension. Therefore, it is possible to estimate the characteristics of brain signals without recording them, which are often costly and time-consuming.

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