A decision support system for the classification of event-related potentials - Vasios, C.E.; Matsopoulos, G.K.; Nikita, K.S.; Uzunoglu, N.; Papageorgiou, C. (Neurel 2002 : 2002 6th Seminar on Neural Network Applications in Electrical Engineering proceedings, September 26-28, 2002, 2002)
In this paper a decision support system (DSS) for the classification of patients on their collected event related potentials (ERPs) is proposed. The DSS consists of two levels: the feature extraction level and the classification level. The feature extraction level comprises the implementation of the multivariate autoregressive model in conjunction with a global optimization method, for the selection of optimum features from ERPs. The classification level is implemented with a single three-layer neural network, trained with the backpropagation algorithm and classifies the data into two classes: patients and control subjects. The DSS has been thoroughly tested to a number of patient data (OCD, FES, depressives and drug users), resulting successful classification up to 100%.