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作 者:徐慕华 周前祥[1] 曹勇[2] 张朋 胡伟[2] Xu Muhua;Zhou Qianxiang;Cao Yong;Zhang Peng;Hu Wei(School of Biological Science and Medical Engineering,Beijing University of Aeronautics and Astronautics,Beijing 100191,China;National Key Laboratory of Human Factors Engineering,China Astronaut Research and Training Center,Beijing 100094,China;Department of Psychology,Capital Normal University,Beijing 101100,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]中国航天员科研训练中心人因工程重点实验室,北京100094 [3]首都师范大学心理学院,北京101100
出 处:《航天医学与医学工程》2024年第1期15-19,37,共6页Space Medicine & Medical Engineering
基 金:载人航天空间医学试验项目(HYZHXM03003)。
摘 要:目的针对航天员在轨期间可能出现的脑力疲劳问题,研究一种适用于空间站环境的脑力疲劳检测方法。方法地基实验采用36h睡眠剥夺实验诱发脑力疲劳状态,采集45名受试者的脑电图(EEG)数据和问卷评分,计算与脑力疲劳相关的一系列EEG特征并运用随机森林分类器构建脑力疲劳检测方法,以区分脑力疲劳水平。结果在地基实验和天基实验的数据中均取得85%以上的平均准确率,各项评价指标趋势一致。结论基于EEG信号的脑力疲劳检测方法能够应对环境及任务的差异,在地基实验与天基实验中均展现出准确稳定的性能,未来在空间飞行环境中的应用具有一定可行性。Objective To develop a mental fatigue detection method for spaceflight environments in response to the mental fatigue problem that may arise during the on-orbit period of astronauts.Methods In the ground-based research,we used a 36-hour sleep deprivation experiment to induce mental fatigue state.Then the electroencephalogram(EEG)data and questionnaire scores were collected from 45 subjects.Finally,a series of EEG features relevant to mental fatigue were calculated and a mental fatigue detection method constructed with Random Forest Classifier to differentiate the mental fatigue level.Results The average accuracy over 85%was achieved in both ground-based and space-based experimental data and each evaluation index had consistent trend.Conclusion The mental fatigue detection method based on EEG signals is suited to the differences in environment and tasks,and shows precise and stable performance in both ground-based experiment and space-based one,which is feasible to be applied in spaceflight environments in the future.
分 类 号:R857.1[医药卫生—航空、航天与航海医学]
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