Self-Regulation Phenomenon Emerged During Prolonged Fatigue Driving: An EEG Connectivity Study

Driving fatigue is a common experience for most drivers and can reduce human cognition and judgment abilities. Previous studies have exhibited a phenomenon of the non-monotonically varying indicators (both behavioral and neurophysiological) for driving fatigue evaluation but paid little attention to...

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Veröffentlicht in:IEEE transactions on neural systems and rehabilitation engineering 2023, Vol.31, p.4895-4906
Hauptverfasser: Li, Gang, Wang, Jie, Xu, Wanxiu, Wu, Kuijun, Liu, Yufeng, Bezerianos, Anastasios, Sun, Yu
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container_title IEEE transactions on neural systems and rehabilitation engineering
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creator Li, Gang
Wang, Jie
Xu, Wanxiu
Wu, Kuijun
Liu, Yufeng
Bezerianos, Anastasios
Sun, Yu
description Driving fatigue is a common experience for most drivers and can reduce human cognition and judgment abilities. Previous studies have exhibited a phenomenon of the non-monotonically varying indicators (both behavioral and neurophysiological) for driving fatigue evaluation but paid little attention to this phenomenon. Herein, we propose a hypothesis that the non-monotonically varying phenomenon is caused by the self-regulation of brain activity, which is defined as the fatigue self-regulation (FSR) phenomenon. In this study, a 90-min simulated driving task was performed on 26 healthy university students. EEG data and reaction time (RT) were synchronously recorded during the whole task. To identify the FSR phenomenon, a data-driven criterion was proposed based on clustering analysis of individual behavioral data and the FSR group was determined as having non-monotonic increase trend of RT and the drops of RT during prolonged driving were more than two levels among the total five levels. The subjects were then divided into two groups: the FSR group and the non-FSR group. Quantitative comparative analysis showed significant differences in behavioral performance, functional connectivity, network characteristics, and classification performance between the FSR and non-FSR groups. Specifically, the behavioral performance exhibited apparent non-monotonic development trend: increasing-decreasing-increasing. Moreover, network characteristics presented similar self-regulated development trends. Our study provides a new insight for revealing the complex neural mechanisms of driving fatigue, which may promote the development of practical techniques for automatic detection method and mitigation strategy.
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Previous studies have exhibited a phenomenon of the non-monotonically varying indicators (both behavioral and neurophysiological) for driving fatigue evaluation but paid little attention to this phenomenon. Herein, we propose a hypothesis that the non-monotonically varying phenomenon is caused by the self-regulation of brain activity, which is defined as the fatigue self-regulation (FSR) phenomenon. In this study, a 90-min simulated driving task was performed on 26 healthy university students. EEG data and reaction time (RT) were synchronously recorded during the whole task. To identify the FSR phenomenon, a data-driven criterion was proposed based on clustering analysis of individual behavioral data and the FSR group was determined as having non-monotonic increase trend of RT and the drops of RT during prolonged driving were more than two levels among the total five levels. The subjects were then divided into two groups: the FSR group and the non-FSR group. 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subjects Accidents
Automobile Driving
Behavioral sciences
brain network
Cluster analysis
Clustering
Cognition
Comparative analysis
Driver fatigue
EEG
Electroencephalography
Electroencephalography - methods
Fatigue
Fatigue - diagnosis
fatigue self-regulation (FSR)
Humans
Indexes
machine learning
Neural networks
Reaction Time - physiology
Reaction time task
Self-Control
Task analysis
Trends
title Self-Regulation Phenomenon Emerged During Prolonged Fatigue Driving: An EEG Connectivity Study
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