Screening for chronic alcoholic subjects using multiple gamma band EEG: a pilot study

Abstract

Electrophysiological impairments of alcoholism have been researched extensively. However, there is none or few reported research on screening methods for chronic alcoholic subjects. Since chronic alcoholics have serious brain dysfunction, a method to screen for them during specific job applications that require good memory, concentration and/or decision making would be useful. In this paper, a method is proposed to discriminate chronic alcoholic from non-alcoholic subjects while they are sober. Energies of electroencephalogram signals in multiple gamma bands recorded while the subjects performed a picture recognition task are used as features by a neural network to detect the chronic alcoholic subjects. Leave one out cross validation strategy reveals that alcoholics could be discriminated from non-alcoholics with accuracy of 94.55%. This pilot study has shown the potential of the method which could be further developed for use in automatic alcoholic screening procedures.