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, J. D R Millán, J. Mouriño, S. Salinari, M. G. Marciani, Fabio Babiloni

Research output: Contribution to journalArticle

Abstract

Objectives: In this paper, we explored the use at 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.

Original languageEnglish
Pages (from-to)337-341
Number of pages5
JournalMethods of Information in Medicine
Volume41
Issue number4
Publication statusPublished - 2002

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Keywords

  • Brain computer interface
  • EEG
  • Imagination of movements
  • Mahalanobis distance
  • Signal space projection

ASJC Scopus subject areas

  • Health Informatics
  • Health Information Management
  • Nursing(all)

Cite this

Cincotti, F., Mattia, D., Babiloni, C., Carducci, F., Bianchi, L., Millán, J. D. R., Mouriño, J., Salinari, S., Marciani, M. G., & Babiloni, F. (2002). Classification of EEG mental patterns by using two scalp electrodes and Mahalanobis distance-based classifiers. Methods of Information in Medicine, 41(4), 337-341.