EEG Analysis of Alcoholics and Controls Based on Feature Extraction

Abstract

In this paper, we investigated EEG feature in the alcoholics and the controls. Principle component analysis was applied to preprocess the original data to reduce the dimensions of EEG. Wavelet transform decomposed the EEGs into five corresponding frequency bands. Power spectrum was estimated in each band. By comparing the power spectrum of the alcoholics and controls in five major frequency bands, we found that increased theta and delta power can be observed obviously in the alcoholics, while alpha power of alcoholics was significantly decreased. In the gamma and beta bands, the power of controls was a little greater than that of alcoholics. The results of the experimental analysis are valuable to alcohol detection and have significance to the brain computer interface research