Author:
Kamaruzzaman Muhammad ‘Afiq Ammar,Othman Marini,Hassan Raini,Abdul Rahman Abdul Wahab,Mahri Nurhafizah
Abstract
Mental fatigue is one of the most typical human infirmities, resulting from an overload of work and lack of sleep which can reduce one’s intellectual resources. Different EEG features have been studied for detecting mental fatigue. This paper characterizes mental fatigue through the understanding of human EEG features for safe driving behaviour and to create an overview of the potential EEG features which are related to mental fatigue. A narrative review approach is employed for describing the neural activity of the human brain in mental fatigue. Specific EEG features in relation to driving tasks, relation to different EEG band waves, pre-processing and feature extraction methods are discussed. From this preliminary work, the increase of parietal alpha power seems to characterize the driver’s mental fatigue in most of the studies. We searched public EEG repositories for identifying potential data sources for our initial study. Finally, we propose a conceptual model that has potentials for identifying mental weariness. In conclusion, future works may involve the identification of other EEG features of higher importance for generalization across study conditions
Reference28 articles.
1. World Health Organization. Global status report on road safety 2015. World Health Organization.
2. F. Wang, J. Lin, W. Wang & H. Wang. EEG-based mental fatigue assessment during driving by using sample entropy and rhythm energy. In Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015 IEEE International Conference on (pp. 1906-1911). IEEE, 2015.
3. E. Grandjean. Fatigue in industry. Occupational and Environmental Medicine 36(3), 175-186, 1979.
4. W. Hu, K. Li, N. Wei, S. Yue, & C. Yin. (2017, October). Influence of exercise-induced local muscle fatigue on the thumb and index finger forces during precision pinch. In Chinese Automation Congress (CAC), 2258-2261, IEEE, 2017.
5. K., Kourakata & Hotta, Y. Muscle fatigue detection during dynamic contraction under blood flow restriction: Improvement of detection sensitivity using multivariable fatigue indices. In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, pp. 6078-6081, IEEE, 2015.
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