[1]赵彦富,随力,李月如.基于脑电图的脑疲劳检测研究进展[J].中国医学物理学杂志,2019,36(11):1312-1316.[doi:DOI:10.3969/j.issn.1005-202X.2019.11.013]
　ZHAO Yanfu,SUI Li,LI Yueru.Progress on brain fatigue detection based on electroencephalogram[J].Chinese Journal of Medical Physics,2019,36(11):1312-1316.[doi:DOI:10.3969/j.issn.1005-202X.2019.11.013]
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基于脑电图的脑疲劳检测研究进展()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
36卷
期数:
2019年第11期
页码:
1312-1316
栏目:
医学信号处理与医学仪器
出版日期:
2019-11-25

文章信息/Info

Title:
Progress on brain fatigue detection based on electroencephalogram
文章编号:
1005-202X（2019）11-1312-05
作者:
赵彦富; 随力; 李月如
上海理工大学医疗器械与食品学院， 上海 200093
Author(s):
ZHAO Yanfu;  SUI Li;  LI Yueru
School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
关键词:
脑疲劳; 脑电图; 小波熵; 人因工程; 综述
Keywords:
brain fatigue;  electroencephalogram;  wavelet entropy;  human factors engineering;  review
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2019.11.013
文献标志码:
A
摘要:
脑疲劳是指在长时间、高强度脑力劳动过程中出现一系列如头痛、记忆力下降、注意力难以集中等不适症状的现象。脑电图（EEG）是通过电极记录下的脑细胞群的自发性、节律性电位活动，其在脑疲劳检测方面发挥着越来越重要的作用。本研究归纳了EEG检测脑疲劳的发展历史，对EEG检测脑疲劳的常用指标：α波相对能量、波形组合参数如（α+θ）/β以及Shannon、二阶和三阶的Renyi、Tsallis和Generalized eScort-Tsallis这5种小波熵进行了介绍，总结了EEG在脑疲劳识别以及人因工程方面的应用，最后分析了EEG在检测脑疲劳方面存在的局限性及其未来的发展趋势。
Abstract:
Brain fatigue refers to a series of symptoms such as headache, memory loss, and difficulty in concentration during long-term and high-intensity mental work. Electroencephalogram (EEG) which is a spontaneous and rhythmic potential activity of brain cell populations recorded by electrodes plays an increasingly important role in brain fatigue detection. Herein the development history of EEG to detect brain fatigue is summarized. Several common indicators for EEG detection of brain fatigue, including α-wave relative energy, waveform combination parameters such as (α+θ)/β and 5 wavelet entropies of Shannon, second- and third-order Renyi, Tsallis and Generalized eScort-Tsallis are introduced. The applications of EEG in brain fatigue recognition and human factors engineering are also reviewed. Finally, the limitations of EEG in detecting brain fatigue and its future development trends are discussed.

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　ZHAO Yanfu,SUI Li,LI Yueru.Progress on brain fatigue detection based on electroencephalogram[J].Chinese Journal of Medical Physics,2019,36(11):1312.[doi:DOI:10.3969/j.issn.1005-202X.2019.11.013]

备注/Memo

备注/Memo:
【收稿日期】2019-06-15 【基金项目】国家自然科学基金（11179015）；上海理工大学科技发展项目（16KJFZ107, 2017KJFZ160） 【作者简介】赵彦富，硕士，研究方向：生物医学工程、神经工程，E-mail: 1264644156@qq.com 【通信作者】随力，博士，教授，研究方向：生物医学工程、神经工程，E-mail: lsui@usst.edu.cn
更新日期/Last Update: 2019-11-28