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Volume 9, Issue 2 (Iranian Journal of Ergonomics 2021)
Iran J Ergon 2021, 9(2): 69-81 |
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Lashgari M, Arab M, Nadjafi M, Maleki A. Correlation Brain Signals and Tractor Sound Signals Based on Fractal Analysis. Iran J Ergon 2021; 9 (2) :69-81
URL: http://journal.iehfs.ir/article-1-788-en.html
URL: http://journal.iehfs.ir/article-1-788-en.html
1- Associate Professor, Department of Biosystems Engineering, Arak University, Arak, Iran , m-lashgari@araku.ac.ir
2- PhD, Department of Medical Engineering, Arak University of Medical Sciences, Arak, Iran
3- Assistant Professor, Department of Electrical Engineering, Arak University of Technology, Arak, Iran
4- Associate Professor, Department of Biosystems Engineering, Shahrekord University, Shahrekord, Iran
2- PhD, Department of Medical Engineering, Arak University of Medical Sciences, Arak, Iran
3- Assistant Professor, Department of Electrical Engineering, Arak University of Technology, Arak, Iran
4- Associate Professor, Department of Biosystems Engineering, Shahrekord University, Shahrekord, Iran
Abstract: (3048 Views)
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.
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.
Type of Study: Research |
Subject:
Other Cases
Received: 2021/01/25 | Accepted: 2021/08/22 | ePublished: 2021/09/21
Received: 2021/01/25 | Accepted: 2021/08/22 | ePublished: 2021/09/21
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