Department of Aerospace Hygiene, Faculty of Aerospace Medicine, Air Force Medical University, Xi'an, China.
Department of Aerospace Medical Equipment, Faculty of Aerospace Medicine, Air Force Medical University, Xi'an, China.
Behav Brain Res. 2023 Feb 13;438:114203. doi: 10.1016/j.bbr.2022.114203. Epub 2022 Nov 7.
A continuous flight task load can induce fatigue and lead to changes in electroencephalography (EEG). EEG microstates can reflect the activities of large-scale neural networks during mental fatigue. This exploratory experiment explored the effects of mental fatigue induced by continuous simulated flight multitasking on EEG microstate indices.
Twenty-four participants performed continuous 2-hour aircraft piloting simulation while EEG were recorded. The Stanford sleepiness scale (SSS) and critical flicker fusion frequency (CFF) were measured before and after the task. Microstate analysis was applied to EEG. Four microstate classes (A-D) were identified during the pre-task, post-task, beginning, and end phases. The effects of mental fatigue were analyzed.
Compared with the pre-task, the post-task had a higher global explained variance (GEV) and time parameters of class C but lower occurrence and coverage of class D. The end had a higher GEV but lower duration and coverage of class D than at the beginning. After 2 h of multitasking, the transition probability between A and D, and between B and D decreased but between A and C increased. Subjective fatigue scores were negatively correlated with occurrence and coverage of class D. Task performance was negatively correlated with duration and coverage of class C but positively correlated with duration and occurrence of class B.
Time parameters and transition probability of EEG microstates can detect mental fatigue induced by continuous aircraft piloting simulation. The global brain network activation of mental fatigue can be detected by EEG microstates that can evaluate flight fatigue.
连续的飞行任务负荷会导致疲劳,并导致脑电图(EEG)的变化。EEG 微观状态可以反映精神疲劳期间大规模神经网络的活动。本探索性实验研究了连续模拟飞行多任务引起的精神疲劳对 EEG 微观状态指标的影响。
24 名参与者在进行 2 小时的飞机驾驶模拟的同时记录 EEG。任务前后分别测量斯坦福嗜睡量表(SSS)和临界闪烁融合频率(CFF)。对 EEG 进行微观状态分析。在任务前、任务后、开始和结束阶段识别四个微观状态类(A-D)。分析精神疲劳的影响。
与任务前相比,任务后 C 类的全局解释方差(GEV)和时间参数更高,但 D 类的出现和覆盖度更低。结束时 GEV 较高,但 D 类的持续时间和覆盖度较低。经过 2 小时的多任务处理后,A 与 D 之间以及 B 与 D 之间的转移概率降低,但 A 与 C 之间的转移概率增加。主观疲劳评分与 D 类的出现和覆盖度呈负相关。任务表现与 C 类的持续时间和覆盖度呈负相关,但与 B 类的持续时间和出现呈正相关。
EEG 微观状态的时间参数和转移概率可以检测连续飞机驾驶模拟引起的精神疲劳。EEG 微观状态可以检测到精神疲劳的大脑全局网络激活,从而评估飞行疲劳。