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Correlation Brain Signals and Tractor Sound Signals Based on Fractal Analysis
Majid Lashgari, Mohammadreza Arab, Mohsen Nadjafi, Ali Maleki,
Volume 9, Issue 2 (10-2021)
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.

A Survey on the Sleep Quality in Agricultural Tractor Drivers in Different Climatic Conditions
Ehsan Houshyar, Hadi Daneshmandi,
Volume 9, Issue 4 (3-2022)
Abstract
Background and Objectives: Among the various agricultural activities, working and driving with farm tractors in different weather conditions lead to fatigue and burnout. The objective of this study was to evaluate the sleep quality of farm tractors drivers in different weather conditions.
Methods: Amongst tractor drivers in Behbahan, Eqlid, and Kavar, 90 participants (Kavar: 27; Eqlid: 33; Behbahan: 30) were selected. The required data was gathered using the demographic characteristics questionnaire and standard questionnaire Pittsburgh Sleep Quality Index (PSQI). We used Kruskal-Wallis and Post-hoc pairwise comparison tests to analyze the data (α = 0.05).
Results: The results showed that there were no significant differences in sleep quality and sleep quality parameters between different region tractors drivers (P > 0.05); but there were significant differences in mental sleep quality (P = 0.001), in terms of delays in falling asleep (P = 0.02), going to sleep duration (P = 0.04) and between Kavar and Behbehan tractor drivers, and also there are significant differences in going to sleep duration (P = 0.04) between Kavar and Eqlid tractor drivers.
Conclusion: Working in critical cold weather (like nights in Eqlid) or critical hot weather (like noon in Behbahan) should be strongly forbidden by providing with a suitable working schedule especially while tractor drivers without driver’s cabin. Drivers’ cabins safeguards drivers against temperature, wind and dust, and, therefore increase their comfort and sleep quality.

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