A decision support system for the classification of event-related potentials

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...

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Published inNeurel 2002 : 2002 6th Seminar on Neural Network Applications in Electrical Engineering proceedings, September 26-28, 2002 pp. 159 - 164
Main Authors Vasios, C.E., Matsopoulos, G.K., Nikita, K.S., Uzunoglu, N., Papageorgiou, C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Brain modeling
Data mining
Decision support systems
Delay estimation
Drugs
Electroencephalography
Enterprise resource planning
Feature extraction
Multi-layer neural network
Neural networks
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ISBN0780375939
9780780375932
DOI10.1109/NEUREL.2002.1057991

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Summary: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%.
ISBN:0780375939
9780780375932
DOI:10.1109/NEUREL.2002.1057991