Drug Abuse Identification based EEG-P300 Amplitude and Latency with Fuzzy Logic Calssifier

The difficulty in detecting drug users is one of the hindrances in overcoming drug abuse. The influence of the drugs on a person's nervous system mainly attacks the brain. If the brain is damaged, it will cause permanent disability and is difficult to repair. In this paper, a classification method to identify a drug user is developed. In the experiment, the drug picture is randomly flashed into the subject to stimuli the drug withdrawal. EEG-P300 potentials which quantified by their amplitude and latency is measured to reflects unique cognitive brain functions. The alteration of the brain activities which represented by amplitude and latency according to the given stimuli among of the selected area is used as a feature for classifier to detect a drug abuser. The recorded brain signals of thirty subjects (addictive, methadone treatment (rehabilitation), and control) were carry out. The classification results using fuzzy logic during withdrawal of drug have demonstrated increases in latencies and decreases amplitudes.