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A self-paced brain - Computer interface for controlling a robot simulator: An online event labelling paradigm and an extended Kalman filter based algorithm for online training

Tsui, CSL and Gan, JQ and Roberts, SJ (2009) 'A self-paced brain - Computer interface for controlling a robot simulator: An online event labelling paradigm and an extended Kalman filter based algorithm for online training.' Medical and Biological Engineering and Computing, 47 (3). 257 - 265. ISSN 0140-0118

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Abstract

Due to the non-stationarity of EEG signals, online training and adaptation are essential to EEG based brain-computer interface (BCI) systems. Self-paced BCIs offer more natural human-machine interaction than synchronous BCIs, but it is a great challenge to train and adapt a self-paced BCI online because the user's control intention and timing are usually unknown. This paper proposes a novel motor imagery based self-paced BCI paradigm for controlling a simulated robot in a specifically designed environment which is able to provide user's control intention and timing during online experiments, so that online training and adaptation of the motor imagery based self-paced BCI can be effectively investigated. We demonstrate the usefulness of the proposed paradigm with an extended Kalman filter based method to adapt the BCI classifier parameters, with experimental results of online self-paced BCI training with four subjects. © International Federation for Medical and Biological Engineering 2009.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 17 Oct 2012 14:45
Last Modified: 17 Aug 2017 18:07
URI: http://repository.essex.ac.uk/id/eprint/4087

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