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Title: Effective user training for motor imagery based brain computer interface with object-directed 3D visual display
Authors: Liang, S
Choi, KS 
Qin, J
Pang, WM
Heng, PA
Issue Date: 2014
Source: Proceedings - 2014 7th International Conference on BioMedical Engineering and Informatics, BMEI 2014, 14-16 October 2014, 7002788, p. 297-301
Abstract: Effective user training could help us to improve the discrimination performance of our intention in brain computer interface (BCI). This paper aims to differentiate users left or right hand motor imagery (MI) tasks with different scenarios in 3D virtual environment, as non-object-directed (NOD) scenario, static-object-directed (SOD) scenario and dynamic-object-directed (DOD) scenario respectively. The results have significant differences by applying these three scenarios. Both SOD and DOD scenarios provide better classification accuracy, shorten single-trial period, and need smaller training samples comparing with the NOD case. We conclude that improving visual display may facilitate learning to use a BCI. Further comparing these results between single-subject and multiple-subject paradigm of BCI, we verify better classification performance could also be achieved by the multiple-subject paradigm. We believe these findings have the potential to improve discrimination performance of users intention for EEG-based BCI applications.
Keywords: Brain computer interface (BCI)
Electroencephalogram (EEG)
Motor imagery
Multiple-subject paradigm
Single-subject paradigm
User training
Visual display
Publisher: Institute of Electrical and Electronics Engineers Inc.
ISBN: 9781479958382
DOI: 10.1109/BMEI.2014.7002788
Appears in Collections:Conference Paper

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