title: [Variance and discriminatory analyses for the classification of wakefulness-dependent EEG patterns].
abstract: 1. To describe 8 alertness-dependent EEG activity patterns to be observed during wakefulness with eyes closed, mean values and standard deviations of the frequencies 4, ..., 13, 14 to 17, 18 to 22 and 23 to 40 c/sec, of the percentage activity in the theta, alpha and beta bands as well as of the theta and alpha amplitudes were calculated. 2. On the basis of 18 variables significant differences between 7 activity patterns were ascertained by means of univariate and multivariate analyses of variance. 3. In the course of stepwise reduction of variables within the framework of a linear discriminatory analysis, an optimal set of variables was determined for the separation of the patterns comprising the following variables: mean value and standard deviation of the alpha amplitudes and mean value of the theta amplitudes as well as the percent quantity of the frequencies 3, ..., 7, 10, 14 to 17 and 23 to 40 c/sec. 4. By means of a linear regression analysis it was shown that the EEG scoring system can be reflected on an interval scale. In connection with results on the reliability of the methods used the results were discussed.
mesh_terms: D000704:Analysis of Variance; D001921:Brain / Q000502:physiology; D004569:Electroencephalography; D006801:Humans; D012044:Regression Analysis; D014851:Wakefulness
vernacular_title: Merkmalscharakteristik und diskriminanzanalytische Klassifikation wachheitsabhängiger EEG-Aktivitätsmuster