2013 Fiscal Year Final Research Report
Neurofeedback training for user adaptation to motor-imagery based BCI
Project/Area Number |
23500483
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Fusional brain recording science
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Research Institution | Tohoku Institute of Technology |
Principal Investigator |
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Co-Investigator(Kenkyū-buntansha) |
KAWASHIMA Ryuta 東北大学, 加齢医学研究所, 教授 (90250828)
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Co-Investigator(Renkei-kenkyūsha) |
YOSHINOBU Tatsuo 東北大学, 大学院・医工学研究科, 教授 (30243265)
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Project Period (FY) |
2011 – 2013
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Keywords | BCI / ニューロフィードバック / 脳波 / NIRS / 大脳運動野 |
Research Abstract |
The BCI (brain-computer interface) based on motor imagery is to detect the intension of subjects from their brain activities from sensorimotor cortex during imagining to move their own limbs. This study aimed to investigate the methodology to use neurofeedback training (NF), on which the processed EEG or NIRS (brain blood flow measured by near-infrared spectroscopy) data is presented to subject in real time, for improving the applicability and accuracy on motor-imagery based BCI. It was found that the motor related EEG on mu, beta and gamma band could be extracted by applying local and sparse spatial filters designed by ICA (independent component analysis) to measured EEG data, and such components could be used for neurofeedback training to improve the performance of motor-imagery based BCI.
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[Book] Towards Practical Brain-Computer Interfaces : Bridging the Gap from Research to Real-World Applications2012
Author(s)
Brunner C., Andreoni G., Bianchi L., Blankertz B., Breitwieser C., Kanoh S., Kothe C.A., Lécuyer A., Makeig S., Mellinger J., Perego P., Renard Y., Schalk G., Susila I.P., Venthur B., Müller-Putz G.R
Total Pages
303-331
Publisher
BCI Software Platform
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