Spatial filtering in the training process of a brain computer interface

Josep Mouriño, José Del R Millán, Febo Cincotti, Silvia Chiappa, Raimon Jané, Fabio Babiloni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The spatial filtering of electroencephalogram data is crucial when analyzing the brain activity. Spatial filters increase the signal-to-noise ratio, thus allowing better classification of the analyzed mental states. This study will show the evolution in the selection of the most appropriate spatial filter when subjects are training to control a brain-computer interface. Different filters -the common average reference and the estimation of the surface Laplacian both using finite different methods and spherical splines- have been adapted and evaluated for a particular configuration of electrodes, using only eight positions: F3, C3, P3, Cz, Pz, F4, C4, and P4.

Original languageEnglish
Title of host publicationAnnual Reports of the Research Reactor Institute, Kyoto University
Pages639-642
Number of pages4
Volume1
Publication statusPublished - 2001
Event23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey
Duration: Oct 25 2001Oct 28 2001

Other

Other23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CountryTurkey
CityIstanbul
Period10/25/0110/28/01

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Keywords

  • Brain-computer interfaces
  • Common average reference
  • Spatial filtering
  • Spherical splines
  • Surface Laplacian

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Mechanical Engineering

Cite this

Mouriño, J., Millán, J. D. R., Cincotti, F., Chiappa, S., Jané, R., & Babiloni, F. (2001). Spatial filtering in the training process of a brain computer interface. In Annual Reports of the Research Reactor Institute, Kyoto University (Vol. 1, pp. 639-642)