Investigation on factors affecting cognitive skills in detection of driving fatigue

Shamsuddin, Syamimi and Ho, Jia Xin and Kamat, Seri Rahayu and Ibrahim, Muhammad Shafiq and Setiawan, Rudi (2025) Investigation on factors affecting cognitive skills in detection of driving fatigue. Journal of Advanced Research in Applied Sciences and Engineering Technology, 51 (2). pp. 270-280. ISSN 2462-1943

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Abstract

Road safety is a worldwide concern where a high number of fatalities and injuries are caused by traffic accidents. One major issue contributing to these incidents is driving while fatigued, which has been recognized as a contributing factor to accidents in many countries. Being tired while driving is a state that encompasses both physical and mental exhaustion and can greatly impair a person's ability to drive safely. Fatigue negatively affects a driver's cognitive abilities, resulting in decreased performance behind the wheel. The aim of this study is to analyse the effect of driving duration, body mass index (BMI), types of roads and gender factor in causing fatigue while driving. Cognitive skills of drivers while driving was measured through the electroencephalogram (EEG) signal gathered from Emotiv EPOC device to measure brain activity. Relationship between cognitive skills and fatigue signalling is then analysed using regression analysis in Design-Expert software. Results indicated that as mental fatigue increases, there is a noticeable decrease in the relative power of beta rhythm, supporting previous research findings. Results on correlation show that the longer the drivers drove, the wearier they become. Obese people experience more fatigue when driving than those with a normal or overweight BMI. Driving on straight roads resulted in greater fatigue compared to driving on winding ones, with female participants indicating higher levels of tiredness than male participants. These insights are crucial for road safety authorities to tailor their supervision methods based on individual characteristics and to design effective driver fatigue warnings.

Item Type:	Article
Uncontrolled Keywords:	Driving fatigue, Regression analysis, Electroencephalogram, Design-expert, Decision making
Divisions:	Faculty Of Industrial And Manufacturing Technology And Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	11 Dec 2025 02:24
Last Modified:	11 Dec 2025 02:24
URI:	http://eprints.utem.edu.my/id/eprint/29166
Statistic Details:	View Download Statistic

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