Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (30): 144-147.

• 数据库、信号与信息处理 • Previous Articles     Next Articles

Analysis of multiparameter electroencephalogram based on wavelet packet for mental fatigue

WANG Peng1,2,CHEN Minyou1,2,FAN Zhaoyong3,GAO Jin4,ZHANG Li1   

  1. 1.College of Electrical Engineering,Chongqing University,Chongqing 400044,China
    2.State Key Laboratory of Power Transmission Equipment & System Security and New Technology,Chongqing 400044,China
    3.Chongqing Electric Power Corporation,Chongqing 400015,China
    4.Chongqing Electric Power Research Institute,Chongqing 401123,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-10-21 Published:2011-10-21

基于小波包变换的精神疲劳多参数脑电分析

王 鹏1,2,陈民铀1,2,范昭勇3,高 晋4,张 莉1   

  1. 1.重庆大学 电气工程学院,重庆 400044
    2.重庆大学 输配电装备及系统安全与新技术国家重点实验室,重庆 400044
    3.重庆电力公司,重庆 400015
    4.重庆电力科学试验研究院,重庆 401123

Abstract: This study is to find the relationships between mental fatigue and parameters of electroencephalogram(EEG),using wavelet packet analysis to calculate the Log energy entropy and to extract basic rhythms from EEG in the state of mental fatigue which is caused by brainwork and sports.Compared with normal state,the EEG from frontal pole of brain presents significant distinction on basic rhythms and log energy entropy in the state of fatigue resulted by brainwork and sports.As conclusion,the relative power in basic rhythms and the log energy entropy can be regarded as valid indices for measuring mental fatigue.

Key words: wavelet packet, Electroencephalogram(EEG), mental fatigue, rhythm extraction, Log energy entropy

摘要: 研究脑力劳动和运动引起的精神疲劳与脑电特征参数之间的相关性,以及这些特征参数在不同状态下的变化规律。通过对两种精神疲劳状态以及不疲劳状态下采集的脑电信号进行小波包分析,提取出脑电各节律并计算脑电对数能量熵,定性分析了各特征参数与不同状态间的关联性。实验结果表明,相较于不疲劳状态而言,前额叶区的脑电各节律相对功率和脑电对数能量熵在两种精神疲劳状态下均有显著变化。因此,前额叶区的脑电各节律相对功率与脑电对数能量熵可以作为衡量精神疲劳的生理指标。

关键词: 小波包, 脑电, 精神疲劳, 节律提取, 对数能量熵