The Influence of Driving Duration, Body Mass Index, Types of Roads and Gender on Decision-Making Skills through β-Waves Analysis in Fatigue Driving
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Abstract
The research on driving fatigue is gaining popularity as the frequency of fatigue-related accidents increases in many countries. However, there has been limited study on the importance of cognitive skills like decision-making skills (DMS) and the variables that influence them in indicating driving fatigue. The study aims to conduct a regression analysis to determine whether variables such as driving duration, body mass index (BMI), types of roads and gender are relevant in influencing DMS and how these variables interact to suggest driving fatigue. Previous research has not examined the combination of these four variables. Materials and methods: DMS was assessed using an electroencephalogram (EEG) through beta, β brain waves. The EEG frequency was recorded for five minutes before driving and completing the driving assignment. The regression analysis was performed using Design Expert software. Results: The Analysis of Variance (ANOVA) found that all variables have Prob > F values less than 0.05, indicating significant effect on β-waves (DMS). Overall, as the driver fatigues, β-waves decrease, indicating an impairment in DMS. β-waves decrease as driving duration and BMI increase due to the stress of dealing with hazardous driving conditions and obesity-related health concerns, respectively. β-waves drop as road geometry changes from winding to monotonous and gender changes from male to female because of physiological signs of boredom generated by road geometry and sex hormone variations, respectively. Conclusion: The findings could be a reference to road safety professionals to control the cause of driving fatigue and hence lower the number of road accidents.
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