Classification of EEG Mental Patterns by Using Two Scalp Electrodes and Mahalanobis Distance-Based Classifiers

F. Cincotti; D. Mattia; C. Babiloni; F. Carducci; L. Bianchi; del R. J. Millán; J. Mouriño; S. Salinari; M. G. Marciani; F. Babiloni

doi:10.1055/s-0038-1634391

Methods of Information in Medicine, Inhaltsverzeichnis

Methods Inf Med 2002; 41(04): 337-341
DOI: 10.1055/s-0038-1634391

Original article

Schattauer GmbH

Classification of EEG Mental Patterns by Using Two Scalp Electrodes and Mahalanobis Distance-Based Classifiers

F. Cincotti

¹IRCCS, Fondazione Santa Lucia, Rome, Italy

,

D. Mattia

¹IRCCS, Fondazione Santa Lucia, Rome, Italy

,

C. Babiloni

²Dip. Fisiologia umana e Farmacologia, Università “La Sapienza”, Rome, Italy

,

F. Carducci

²Dip. Fisiologia umana e Farmacologia, Università “La Sapienza”, Rome, Italy

,

L. Bianchi

³Dip. Neuroscienze, Università “Tor Vergata”, Rome, Italy

,

del R. J. Millán

⁴ISIS, Joint Research Center of the EC, Ispra (VA), Italy

,

J. Mouriño

⁴ISIS, Joint Research Center of the EC, Ispra (VA), Italy

,

S. Salinari

⁵Dipartimento Informatica e Sistemistica, Università “La Sapienza”, Rome, Italy

,

M. G. Marciani

¹IRCCS, Fondazione Santa Lucia, Rome, Italy

³Dip. Neuroscienze, Università “Tor Vergata”, Rome, Italy

,

F. Babiloni

²Dip. Fisiologia umana e Farmacologia, Università “La Sapienza”, Rome, Italy

› Institutsangaben

Abstract

Summary

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

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Referenzen

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