Self-paced BCI using multiple SWT-based classifiers

TitleSelf-paced BCI using multiple SWT-based classifiers
Publication TypeConference Paper
Year of Publication2008
AuthorsFaradji, F., R. K. Ward, and G. E. Birch
Conference NameEngineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Pagination2095 -2098
Date Publishedaug.
KeywordsAlgorithms, Computer-Assisted, electroencephalography, Evoked Potentials, Humans, Neural Networks (Computer), signal processing, User-Computer Interface, Visual

The presence of false activations inhibits the use of existing self-paced BCIs in real life applications. We present a new design method for a self-paced BCI that yielded 0% false activations using the data of two subjects. This system obtains templates/shapes of the movement related finger flexion patterns. To obtain the templates, the intentional control data are decomposed into 5 levels using the stationary wavelet transform. Then, ensemble averaging is done. These templates are used to train 5 radial basis function neural networks. This is followed by a majority voting classifier.


a place of mind, The University of British Columbia

Electrical and Computer Engineering
2332 Main Mall
Vancouver, BC Canada V6T 1Z4
Tel +1.604.822.2872
Fax +1.604.822.5949

Emergency Procedures | Accessibility | Contact UBC | © Copyright 2021 The University of British Columbia