基于脑电图的脑疲劳检测研究进展

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。

Progress on brain fatigue detection based on electroencephalogram

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.