Classification of EEG mental patterns by using two scalp electrodes and Mahalanobis distance-based classifiers
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Updated: Sep 28, 2026
Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
Published on: July 26, 2013
F Cincotti1, D Mattia, C Babiloni
1IRCCS, Fondazione Santa Lucia, Rome, Italy.
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.
