02116nas a2200277 4500008004100000022001400041245011300055210006900168260001200237300001500249490000700264520130300271653001001574653002701584653001201611653001101623653000901634653001901643653004101662653001601703100001801719700002001737700001801757700001501775856004801790 2009 eng d a1001-551500aPower spectrum analysis on the multiparameter electroencephalogram features of physiological mental fatigue.0 aPower spectrum analysis on the multiparameter electroencephalogr c02/2009 a162-6, 1720 v263 a
The aim of this experiment is to find a feasible impersonal index for analyzing the physiological mental fatigue level. Three characteristic parameters, relative power in different rhythm, barycenter frequency and power spectral entropy, are extracted from two channels' electroencephalogram (EEG) under two physiological mental fatigue states. Then relationships between such three parameters and physiological mental fatigue are analyzed to explore whether they can be of use for detecting (or monitoring) the mental fatigue level. The experiment results show that the relative power, barycenter frequency and power spectral entropy of EEG exhibit strong correlation with physiological mental fatigue level. While physiological mental fatigue level increases, the relative power in theta, alpha and beta rhythms, barycenter frequency and power spectral entropy of EEG decrease, but the relative power in delta rhythm of EEG increases. The relative power in four rhythms, barycenter frequency and power spectral entropy of EEG reflect the change of physiological mental fatigue level sensitively, and may hopefully be used as indexes for detecting physiological mental fatigue level.
10aAdult10aElectroencephalography10aEntropy10aHumans10aMale10aMental Fatigue10aSignal Processing, Computer-Assisted10aYoung Adult1 aZhang, Ai-hua1 aZheng, Shi Dong1 aPei, Xiao-Mei1 aOuyang, Yi uhttp://www.ncbi.nlm.nih.gov/pubmed/19334577