Development of EEG Biomarker for Detection of Alcoholism

Abstract

Detection and analysis of alcoholism using the Electroencephalogram signal is newlinean active research topic over the last decade, and the technology has gradually matured newlinefor its use in real-time applications. EEG based screening of alcoholism is a noninvasive newlinemethod for the detection of alcoholism. This technology is prominently used in the rehabilitation center to detect the level of alcoholism. Further, it may be used as one of newlinethe psychometric tests during recruitment in the public and the private sector. newlineIn traditional methodology, questionnaires and blood test-based approaches are used newlinefor identifying the level of alcoholism in a subject under test. However, a blood test is newlineinvasive and requires high support from the subject under test. Questionnaires based newlinemethod is subject dependent. Generally, subjects under test tend to hide their alcoholism by fake responses. Today, almost all rehabilitation centers use a similar program newlinefor all the patients (irrespective of their drinking level). newlineSeveral feature extraction methods have been reported for the detection of alcoholism. newlineThese methods extract features directly from the EEG signal. However, the EEG signal newlinecan be decomposed into several rhythms, and then features can be extracted from each newlinerhythm. newlineIn this thesis, an attempt is made to project a novel method for the detection of alcoholism based on selecting the optimal channels that are sufficient and necessary for the newlinedetection of alcoholism. Further, detection of alcoholism level has investigated in the newlinethesis.