Fisher Discriminant Analysis of EEG Data based on Drinking Events
نویسنده
چکیده
Objective: We have performed Fisher’s discriminant analysis to the EEG data of experimental subjects who were drunk on alcohol. The subjects of these experiments were recorded anonymously. The data has been used for feature extraction and classification decisions in order to determine the part of head electrode’s categories after alcohol intake and to explore the changes of EEG features. The calculation methods have been divided into four species In accordance with the strength of wave. The head electrodes have been used as a part of of 21 electrodes EEG data used for 6 subjects. We have performed Fisher’s discriminant analysis of the EEG data on the six subjects. After every 20 minutes 7.2 ml of alcohol was given to the subjects for drinking. The EEG data processing and statistical analysis adopted was independently designed regarding the EEG analysis toolbox and the program for correlation analysis. Results of the Fisher discriminant would be better applied to the feature extraction and classification decisions of the EEG data. Conclusions: EEG activity shows a significant response after alcohol intakes, electrode categories is noted to constantly change. After drinking 200 ml categories changes obviously, and drinking 600 ml category changes become calm. The changes found are not so obvious in men but are significantly obvious in women.
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تاریخ انتشار 2015