Key result
Sleep deprivation-induced fatigue in human drivers was traced by analyzing the variation of connectivity between brain areas using EEG state-space analysis.
Observational
EEG state-space analysis using the S-Estimator technique can quantify brain synchronization to trace advancing fatigue levels in sleep-deprived drivers.
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May aid EEG-based fatigue monitoring in drivers; hypothesis-generating and requires prospective validation before any clinical use.
Electroencephalogram (EEG) is widely used to predict performance degradation of human subjects due to mental or physical fatigue. Analysis of fatigue due to sleep deprivation using EEG synchronization is a promising field of research. The present paper analyses advancing levels of fatigue in human drivers in a sleep-deprivation experiment by studying the synchronization between EEG data recorded from various brain areas. The S-Estimator technique based on state-space analysis has been employed to quantify the synchronization between EEG channels, which has then been formulated in terms of a complex network. The change in the parameters of the network has been analyzed to find the variation of connectivity between brain areas and hence to trace the increase in fatigue levels of the subjects.
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Sengupta et al. (2014) conducted an observational in Fatigue due to sleep deprivation. Sleep deprivation was evaluated on Variation of connectivity between brain areas and increase in fatigue levels. Sleep deprivation-induced fatigue in human drivers was traced by analyzing the variation of connectivity between brain areas using EEG state-space analysis.
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