Softmax discriminant classifier for detection of risk levels in alcoholic EEG signals

In various societies, alcoholic beverages are widely used. A good and healthy lifestyle can be leaded if the consumption of alcohol is minimal and occasional. However, with the over intake of alcohol, it disturbs the decision making process of the person and it leads to severe mental, physical and emotional health problems. The alcohol detection level is important to determine the person's capability to do a particular job. In this paper, Softmax Discriminant Classifier (SDC) is employed to detect the risk level of a single chronic alcoholic patient from Electroencephalography (EEG) Signals. Results show that an average Perfect Classification rate of 72.70%, an average Performance Index of 62.00% along with an average classification accuracy of about 86.35% is obtained.