Key result
During a 90-minute simulated driving task, 18 of 26 participants exhibited a fatigue self-regulation phenomenon characterized by a non-monotonic trend in reaction time and distinct brain network reorganization.
Observational (n=26)
No
The study identifies a fatigue self-regulation phenomenon during prolonged driving, characterized by non-monotonic changes in reaction time and EEG network characteristics.
Answers are grounded in this paper and cite their sources.
May caution against linear fatigue models in driver monitoring; leaves open empirical validation of FSR mechanisms.
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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Li et al. (2023) conducted an observational in Driving fatigue (n=26). Prolonged simulated driving task vs. Non-FSR (fatigue self-regulation) group was evaluated on Reaction time (RT) in the Fatigue Deepening State (FDS) (p=<0.05). During a 90-minute simulated driving task, 18 of 26 participants exhibited a fatigue self-regulation phenomenon characterized by a non-monotonic trend in reaction time and distinct brain network reorganization.
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