A brain-computer interface based on functional transcranial doppler ultrasound using wavelet transform and support vector machines

A brain-computer interface based on functional transcranial doppler ultrasound using wavelet... •We investigated the feasibility of a 2-class and 3-class real-time BCI system.•Three mental tasks that induce different blood flow velocities were employed.•Statistical features for wavelet transform coefficients were calculated.•Wilcoxon test and SVM were used for feature selection and classification.•Bit rates exceeding 3 bits/min were achieved. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Neuroscience Methods Elsevier

A brain-computer interface based on functional transcranial doppler ultrasound using wavelet transform and support vector machines

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0165-0270
eISSN
1872-678X
D.O.I.
10.1016/j.jneumeth.2017.10.003
Publisher site
See Article on Publisher Site

Abstract

•We investigated the feasibility of a 2-class and 3-class real-time BCI system.•Three mental tasks that induce different blood flow velocities were employed.•Statistical features for wavelet transform coefficients were calculated.•Wilcoxon test and SVM were used for feature selection and classification.•Bit rates exceeding 3 bits/min were achieved.

Journal

Journal of Neuroscience MethodsElsevier

Published: Jan 1, 2018

References

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