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Published in: Medical & Biological Engineering & Computing 12/2009

01-12-2009 | Original Article

Identification of task parameters from movement-related cortical potentials

Authors: Ying Gu, Omar Feix do Nascimento, Marie-Françoise Lucas, Dario Farina

Published in: Medical & Biological Engineering & Computing | Issue 12/2009

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Abstract

The study investigates the accuracy in discriminating rate of torque development (RTD) and target torque (TT) (task parameters) from electroencephalography (EEG) signals generated during imaginary motor tasks. Signals were acquired from nine healthy subjects during four imaginary isometric plantar-flexions of the right foot involving two RTDs (ballistic and moderate) and two TTs (30 and 60% of the maximal voluntary contraction torque), each repeated 60 times in random order. The single-trial EEG traces were classified with a pattern recognition approach based on wavelet coefficients as features and support vector machine (SVM) as classifier. Average misclassification rates were (mean ± SD) 16 ± 9% and 26 ± 13% for discrimination of the two TTs under ballistic and moderate RTDs, respectively. RTDs could be discriminated with misclassification rates of 16 ± 11% and 19 ± 10% under high and low TT, respectively. These results indicate that differences in both TT and RTD can be detected from single-trial EEG traces during imaginary tasks.

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Metadata
Title
Identification of task parameters from movement-related cortical potentials
Authors
Ying Gu
Omar Feix do Nascimento
Marie-Françoise Lucas
Dario Farina
Publication date
01-12-2009
Publisher
Springer-Verlag
Published in
Medical & Biological Engineering & Computing / Issue 12/2009
Print ISSN: 0140-0118
Electronic ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-009-0523-3

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