Classification of EEG Mental Patterns by Using Two Scalp Electrodes and Mahalanobis Distance-Based Classifiers - Cincotti, F.; Mattia, D.; Babiloni, C.; Carducci, F.; Bianchi, L.; Millán, del R. J.; Mouriño, J.; Salinari, S.; Marciani, M. G.; Babiloni, F. (Methods of Information in Medicine, 2002)
Objectives: In this paper, we explored the use of quadratic classifiers based on Mahalanobis distance to detect mental EEG patterns from a reduced set of scalp recording electrodes.Methods: Electrodes are placed in scalp centro-parietal zones (C3, P3, C4 and P4 positions of the international 10-20 system). A Mahalanobis distance classifier based on the use of full covariance matrix was used.Results: The quadratic classifier was able to detect EEG activity related to imagination of movement with an affordable accuracy (97% correct classification, on average) by using only C3 and C4 electrodes.Conclusions: Such a result is interesting for the use of Mahalanobis-based classifiers in the brain computer interface area.
Keywords: Brain computer interface; signal space projection; Mahalanobis distance; EEG; imagination of movements