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Model-Based Approach to EEG Classification
Engineering Education # 04, April 2014
DOI: 10.7463/0414.0705745
The paper offers a developed method of constructing a feature space for electroencephalogram classification. It is based on the localization of brain’s electrical activity sources. The simplest statistical characteristics of dipole moments for equivalent current dipoles are chosen as features for classification, and the nearest neighbour algorithm is used for classification. The research on real electroencephalograms reveals that the accuracy of the proposed method is comparable to the accuracy of the existing classical approaches in brain-computer interfaces at the same time giving a number of opportunities to further increase it and having clear neurophysiological interpretation.
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