alexa Single-trial classification of vowel speech imagery using common spatial patterns.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Computer Science & Systems Biology

Author(s): DaSalla CS, Kambara H, Sato M, Koike Y

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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. This article was published in Neural Netw and referenced in Journal of Computer Science & Systems Biology

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