Enhancing training performance for brain–computer interface with object-directed 3D visual guidance

Purpose The accuracy of the classification of user intentions is essential for motor imagery (MI)-based brain–computer interface (BCI). Effective and appropriate training for users could help us produce the high reliability of mind decision making related with MI tasks. In this study, we aimed to in...

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Bibliographic Details
Published in:	International journal for computer assisted radiology and surgery Vol. 11; no. 11; pp. 2129 - 2137
Main Authors:	Liang, Shuang, Choi, Kup-Sze, Qin, Jing, Pang, Wai-Man, Heng, Pheng-Ann
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2016 Springer Nature B.V
Subjects:	Adult Brain-Computer Interfaces Classification Computer Imaging Computer Science Electroencephalography - methods Female Health Informatics Human-computer interface Humans Imaging Male Medicine Medicine & Public Health Original Article Patient Education as Topic Pattern Recognition and Graphics Radiology Reproducibility of Results Surgery Virtual environments Vision Visual effects Electroencephpalogram (EEG) Visual guidance User training Single-subject paradigm Motor imagery Multi-subject paradigm Brain–computer interface (BCI)
ISSN:	1861-6410, 1861-6429, 1861-6429
Online Access:	Get full text
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