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

  • Autores: Ramaswamy Palaniappan
  • Localización: Journal of Computer Science and Technology, ISSN-e 1666-6038, Vol. 7, Nº. 2, 2007 (Ejemplar dedicado a: Twentieth Issue), págs. 182-185
  • Idioma: inglés
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  • Resumen
    • 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.


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