北京航空航天大学学报 ›› 2016, Vol. 42 ›› Issue (7): 1406-1413.doi: 10.13700/j.bh.1001-5965.2015.0428

• 论文 • 上一篇    下一篇

基于EEG的脑力疲劳特征研究

范晓丽1, 牛海燕2, 周前祥1, 柳忠起1   

  1. 1. 北京航空航天大学生物与医学工程学院, 北京 100083;
    2. 北京特种车辆研究所, 北京 100072
  • 收稿日期:2015-06-26 出版日期:2016-07-20 发布日期:2016-07-29
  • 通讯作者: 周前祥,Tel.: 010-82338696 E-mail: zqxg@buaa.edu.cn E-mail:zqxg@buaa.edu.cn
  • 作者简介:范晓丽 女,博士研究生。主要研究方向:航空航天人因工程。Tel.: 18810152142 E-mail: fanfan19851414@163.com;周前祥 男,博士,教授,博士生导师。主要研究方向:航空航天人因工程。Tel.: 010-82338696 E-mail: zqxg@buaa.edu.cn
  • 基金资助:
    国家自然科学基金(31170895);国防预研基金(A0920132003);中国航天员中心人因工程重点实验室开放课题(HF2013-K-06)

Mental fatigue characteristics based on EEG analysis

FAN Xiaoli1, NIU Haiyan2, ZHOU Qianxiang1, LIU Zhongqi1   

  1. 1. School of Biology and Medical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
    2. Beijing Special Vehicle Research Institute, Beijing 100072, China
  • Received:2015-06-26 Online:2016-07-20 Published:2016-07-29

摘要: 模拟飞行员在飞行过程中监视仪表信息的过程,分析脑电(EEG)随脑力疲劳变化的特点及规律,从而为后期对抗脑力疲劳提供科学根据。通过设计2级不同难度的视觉监控任务分别诱发脑力疲劳,采用多种方法相结合进行研究,比较EEG参数(δ、θ、α、β、(α+θ)/βα/β、(α+θ)/(α+β)和 θ/β)在任务前后的变化情况。结果表明:从正常到疲劳状态,额区、中央区、顶区和枕区的α波相对能量显著增加(P < 0.05);前额区、侧额区、后颞区以及枕区的β波相对能量显著降低(P < 0.05);δ波和θ波相对能量变化未达到显著性差异(均有P > 0.05);参数(α+θ)/βα/β、(α+θ)/(α+β)和θ/β在除颞区外的各脑区都显著增大(P < 0.05);在颞区,只有α/β在疲劳前后增加明显(P < 0.05);与较高难度的任务比较,低难度任务中的各EEG参数变化较为明显。因此,除δ波和θ波以外的其他特征参数被证实在特定的脑区域可以作为衡量脑力疲劳的潜在指标,同时可以验证适当地增加任务难度可以在某种程度上对抗脑力疲劳的产生。

关键词: 脑力疲劳, 任务难度, 视觉监控, 脑电(EEG), 小波分析

Abstract: By simulating the process of pilots monitoring instrument information during flight,the change characteristics of electroencephalogram (EEG) waves along with mental fatigue were analyzed,which will provide scientific bases for future development of countermeasure to fatigue.Two visual detection tasks of different difficulties were designed to induce fatigue respectively,and many measurements were combined to study the EEG characteristics of fatigue.The EEG parameters [δ,θ,α,β,(α+θ)/β,α/β,(α+θ)/(α+β),θ/β] at the beginning and end sections of the task were compared and analyzed.The results show that there is a significant increase in α activity in the frontal,central,parietal and occipital lobes(P < 0.05),and a decrease in the β activity in the pre-frontal,inferior frontal,posterior temporal and occipital lobes(P < 0.05); there is no significant difference in δ rhythm and θ rhythm in any brain region(all in P > 0.05); The four formulas increase significantly in all brain regions except the temporal(P < 0.05),where only α/β changes clearly(P < 0.05); compared with the task with higher difficulty,the parameters in the task of lower difficulty change more obviously.Therefore,all these characteristic parameters in specific brain regions except for δ and θ can be considered as possible indicators for mental fatigue.It was also verified that adding right amount of task difficulty could counter mental fatigue.

Key words: mental fatigue, task difficulty, visual detection, electroencephalogram (EEG), wavelet analysis

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