EEG waveband ratios and Shannon's entropy show potential as indicators for detecting and evaluating mental fatigue.
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EEG metrics may aid objective fatigue detection; leaves open validation beyond controlled tasks.
Mental fatigue is considered to be a contributing factor responsible for numerous road accidents and various medical conditions and the efficiency and performance could be impaired during fatigue. Hence, determining how to evaluate mental fatigue is very important. In the present study, ten subjects performed a long-term visual search task with electroencephalogram recorded, and self-assessment and reaction time (RT) were combined to verify if mental fatigue had been induced and were also used as confirmatory tests for the proposed measures. The changes in relative energy in four wavebands (δ,θ,α, and β), four ratio formulas [(α+θ)/β,α/β,(α+θ)/(α+β), and θ/β], and Shannon's entropy (SE) were compared and analyzed between the beginning and end of the task. The results showed that a significant increase occurred in alpha activity in the frontal, central, posterior temporal, parietal, and occipital lobes, and a dip occurred in the beta activity in the pre-frontal, inferior frontal, posterior temporal, and occipital lobes. The ratio formulas clearly increased in all of these brain regions except the temporal region, where only α/β changed obviously after finishing the 60-min visual search task. SE significantly increased in the posterior temporal, parietal, and occipital lobes. These results demonstrate some potential indicators for mental fatigue detection and evaluation, which can be applied in the future development of countermeasures to fatigue.
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Fan et al. (2015) studied this question.
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