Spatial Filtering in the Training Process of a Brain Computer Interface

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.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412411

Entities

People

  • Febo Cincotti
  • Jose Del Millan
  • Josep Mourino
  • Raimon Jane
  • Silvia Chiappa

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Boundaries
  • Classification
  • Computers
  • Data Acquisition
  • Electrodes
  • Electroencephalography
  • Equations
  • Feedback
  • Filters
  • Filtration
  • Frequency
  • Frequency Bands
  • Mathematical Models
  • Power Spectra
  • Recognition
  • Spatial Filtering

Readers

  • Approximation Theory.
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • Fully Networked C3
  • Fully Networked C3 - Command and Control