A motor imagery BCI experiment using wavelet analysis and spatial patterns feature extraction

Obed Carrera-León, Juan Manuel Ramirez, Vicente Alarcon-Aquino, Mary Baker, David D'Croz-Baron, Pilar Gomez-Gil

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

16 Scopus citations

Abstract

A brain computer interface (BCI) is a system that aims to control devices by analyzing brain signals patterns. In this work, a convenient time-frequency representation (TFR) for visualizing ERD/ERS phenomenon (Event related synchronization and desynchronization) based on Hilbert transform and spatial patterns is addressed, and a wavelet based feature extraction method for motor imagery tasks is presented. The feature vectors are constructed with four statistical and energy parameters obtained from wavelet decomposition, based on the sub-band coding algorithm. Experimentation with three classification methods for comparison purposes was carried out using Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), and Support Vector Machine (SVM). In each case, ten-fold validation is used to obtain average misclassification rates.

Original languageEnglish
Title of host publication2012 Workshop on Engineering Applications, WEA 2012
DOIs
StatePublished - 2012
Event2012 Workshop on Engineering Applications, WEA 2012 - Bogota D.C., Colombia
Duration: May 2 2012May 4 2012

Publication series

Name2012 Workshop on Engineering Applications, WEA 2012

Conference

Conference2012 Workshop on Engineering Applications, WEA 2012
CountryColombia
CityBogota D.C.
Period05/2/1205/4/12

Keywords

  • BCI
  • EEG
  • LDA
  • Support Vector Machine
  • Wavelet (DWT)

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