基于EEG的飞行员脑力疲劳评估研究进展  

Research Progress of Pilots’Mental Fatigue Evaluation Based on EEG

作　　者：韩明秀 王盛 王煜文 牛海军[1] 柳忠起[1] 刘涛 HAN Mingxiu;WANG Sheng;WANG Yuwen;NIU Haijun;LIU Zhongqi;LIU Tao(School of Biological Science and Medical Engineering,Beihang University,Beijing 100191,China;Shanghai Aviation Electric Co.,Ltd,Shanghai 201100,China)

机构地区：[1]北京航空航天大学生物与医学工程学院,北京100191 [2]上海航空电器有限公司,上海201100

出　　处：《载人航天》2021年第5期639-645,共7页Manned Spaceflight

基　　金：国家重点研发计划课题(2019YFC0118602)。

摘　　要：脑力疲劳是导致飞行事故的主要原因之一,脑电(EEG)技术广泛应用于飞行员的脑力疲劳研究领域。从脑力疲劳的类型、分级方法和神经机制角度,阐明飞行员脑力疲劳的本质,综述了基于EEG技术探究飞行员脑力疲劳的研究结果。EEG研究表明:α和θ节律的激活强度对脑力疲劳水平的变化敏感,4种节律的比值在疲劳评估方面效果更好;机器学习方法和非线性特性方法都可以较准确地监测疲劳水平,基于多模态电生理信息构建的脑力疲劳分类模型准确率更高、性能更稳定。Mental fatigue is one of the main causes of flight accidents,and EEG technology is widely used in the field of pilots’mental fatigue research.In this article,the nature of pilots’mental fa-tigue was clarified from the perspective of the types,classification methods and neural mechanisms of mental fatigue,and the research results based on EEG technology to explore the mental fatigue of pi-lots were summarized.EEG studies showed that the activation intensity ofαandθrhythms was sen-sitive to changes in mental fatigue,and the ratio of the four rhythms was more effective in fatigue as-sessment.Both machine learning methods and nonlinear characteristics methods could accurately mo-nitor fatigue,and the fatigue monitoring model constructed based on multi-modal electrophysiological information had higher accuracy and more stable performance.

关 键 词：飞行员 脑力疲劳 神经机制 脑电 多模态电生理信息 

分 类 号：R857[医药卫生—航空、航天与航海医学]