DocumentCode :
527735
Title :
The training strategy in brain-computer interface
Author :
Xia, Bin ; Yang, Wenlu ; Xiao Dianyun ; Wang Cong
Author_Institution :
Coll. of Electron. & Inf. Eng., Tongji Univ., Shanghai, China
Volume :
4
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
2190
Lastpage :
2193
Abstract :
In this paper, we discuss the different train strategies for brain-computer interface. In general, it will take a long time to train subjects for motor imagery based BCI. There are many biofeedback methods to train subject. To compare the efficiency of different training strategies, we train the subjects by using two type training models: virtual reality and progress bar. The progress bar based training strategy show good result in our experiments.
Keywords :
brain-computer interfaces; virtual reality; biofeedback methods; brain-computer interface; motor imagery; progress bar based training strategy; training strategy; virtual reality; Accuracy; Electroencephalography; Feature extraction; Signal processing; Support vector machines; Training; Virtual reality; motor imagery; progress bar; virtual-reality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5583993
Filename :
5583993
Link To Document :
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