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Single-trial classification of vowel speech imagery using common spatial patterns

Authors
Journal
Neural Networks
0893-6080
Publisher
Elsevier
Publication Date
Volume
22
Issue
9
Identifiers
DOI: 10.1016/j.neunet.2009.05.008
Keywords
  • Eeg
  • Vowel
  • Speech
  • Imagery
  • Csp
Disciplines
  • Communication
  • Design

Abstract

Abstract With the goal of providing a speech prosthesis for individuals with severe communication impairments, we propose a control scheme for brain–computer interfaces using vowel speech imagery. Electroencephalography was recorded in three healthy subjects for three tasks, imaginary speech of the English vowels /a/ and /u/, and a no action state as control. Trial averages revealed readiness potentials at 200 ms after stimulus and speech related potentials peaking after 350 ms. Spatial filters optimized for task discrimination were designed using the common spatial patterns method, and the resultant feature vectors were classified using a nonlinear support vector machine. Overall classification accuracies ranged from 68% to 78%. Results indicate significant potential for the use of vowel speech imagery as a speech prosthesis controller.

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