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Detecting Drug Use based on P300 Potential Amplitude and Latency Feature with Fuzzy Logic Classifier

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Abstract

Drug addiction is a complex disease process of the brain that results from recurring drug intoxication. The randomly flashed of the drug picture is used to stimuli the drug withdrawal. EEG-P300 potentials which generally quantified by their amplitude and latency measures to reflects unique cognitive brain functions is used as a feature for classifier to detect a drug addiction. Examinations of thirty subjects (consist of three group: addictive, methadone treatment (rehabilitation), and control (normal)) were performed. Statistical analysis was performed for the extracted amplitude and latency. The higher average amplitude is obtained from the addiction subjects and the longer average latency is obtained from non-addiction subject. P300 measurements during withdrawal of drug have demonstrated increases in latencies and decreases amplitudes

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