2022
DOI: 10.3390/e24081093
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Directed Brain Network Analysis for Fatigue Driving Based on EEG Source Signals

Abstract: Fatigue driving is one of the major factors that leads to traffic accidents. Long-term monotonous driving can easily cause a decrease in the driver’s attention and vigilance, manifesting a fatigue effect. This paper proposes a means of revealing the effects of driving fatigue on the brain’s information processing abilities, from the aspect of a directed brain network based on electroencephalogram (EEG) source signals. Based on current source density (CSD) data derived from EEG signals using source analysis, a … Show more

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Cited by 8 publications
(5 citation statements)
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“…First, there was lower connectivity in the occipital region in the drowsy state. This finding was consistent with the findings in [55]- [58], which might be an indication of fading of consciousness [59]. Second, there was higher connectivity in the parietal region in the alert state.…”
Section: B Interpretability Analysissupporting
confidence: 91%
“…First, there was lower connectivity in the occipital region in the drowsy state. This finding was consistent with the findings in [55]- [58], which might be an indication of fading of consciousness [59]. Second, there was higher connectivity in the parietal region in the alert state.…”
Section: B Interpretability Analysissupporting
confidence: 91%
“…Sadly, however, current studies are more based on the role of Markov blankets on in- and out-degree, multivariate non-parametric dynamic Granger causality with directed transfer functions to build directed weighted networks ( Lewis et al, 2009 ; Horvát et al, 2016 ; Zafeiriou et al, 2020 ). Next, graph-theoretic analysis techniques, such as typical path length, global efficiency, local efficiency, and clustering coefficients ( Rentzeperis and van Leeuwen, 2020 ; Friston et al, 2021 ; Qin et al, 2022 ), were applied to the network. It is pleasant to observe that our analysis of directed networks utilizing the eigenmodal technique is relatively novel.…”
Section: Discussionmentioning
confidence: 99%
“…Therefore, It is often used as an adjunct to detect driver fatigue [3]. The latter mainly involves feature extraction and analysis of EEG signals, electromyogram, electrocardiogram and electrooculogram, which is generally accepted by researchers and widely used in driver fatigue detection method [4].…”
Section: Introductionmentioning
confidence: 99%