Abstract
In this paper, we evaluated BCI algorithm using CSP for finding out about realistic possibility of BCI based on neurofeedback. BCI algorithm that was comprised of CSP and 3 kinds of classifier such as least square linear classifier, SVM and linear discriminant analysis was evaluated in 10 people. According to the result of the experiment, the effect of neurofeedback is evaluated. And in case of neurofeedback, some subject is exceptional but general trend shows the performance improvement by neurofeedback. This study gives the need for adaptive evaluation of motor imagery using neurofeedback based EEG-BCI that can be related to generic and robust system for automated subject-specific classification of EEG based BCI system, development of EEG based BCI literacy performance evaluation system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ryu, Y.S., Lee, Y.B., Jeong, W.J., Lee, S.J., Kang, D.H., Lee, M.H. (2011). Cross Evaluation for Characteristics of Motor Imagery Using Neuro-feedback Based EEG-Brain Computer Interface. In: Osman, N.A.A., Abas, W.A.B.W., Wahab, A.K.A., Ting, HN. (eds) 5th Kuala Lumpur International Conference on Biomedical Engineering 2011. IFMBE Proceedings, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21729-6_126
Download citation
DOI: https://doi.org/10.1007/978-3-642-21729-6_126
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21728-9
Online ISBN: 978-3-642-21729-6
eBook Packages: EngineeringEngineering (R0)