EEG Features for Driver’s Mental Fatigue Detection: A Preliminary Work

Authors

  • Muhammad ‘Afiq Ammar Kamaruzzaman International Islamic University Malaysia
  • Marini Othman International Islamic University Malaysia
  • Raini Hassan International Islamic University Malaysia
  • Abdul Wahab Abdul Rahman International Islamic University Malaysia
  • Nurhafizah Mahri International Islamic University Malaysia

DOI:

https://doi.org/10.31436/ijpcc.v9i1.355

Keywords:

EEG sensor, psychological fatigue, driver's fatigue, traffic safety

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

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Published

2023-01-28

How to Cite

Kamaruzzaman, M. ‘Afiq A. ., Othman, M., Hassan, R., Abdul Rahman, A. W., & Mahri, N. (2023). EEG Features for Driver’s Mental Fatigue Detection: A Preliminary Work. International Journal on Perceptive and Cognitive Computing, 9(1), 88–94. https://doi.org/10.31436/ijpcc.v9i1.355

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