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Paper Abstract and Keywords
Presentation 2014-06-13 09:25
Development of a Training Strategy for Electroencephalogram Control Using a Brain-Computer Interface Driven Wheelchair.
Yuki Temma, Shun Matsumoto, Kan Matsubara, Yasunari Hashimoto (Kitami Inst. of Tech.) MBE2014-13
Abstract (in Japanese) (See Japanese page) 
(in English) Brain-computer (Brain-machine) interfaces (BCIs or BMIs) are developed to translate the electroencephalogram (EEG) recorded from a BCI user’s scalp into signals for control of external devices. BCIs have been expected as being useful interfaces for severely motor-impaired patients, especially, a BCI-driven motor-wheelchair is expected to allows such patients to move just by their remained brain activities. The purposes of this study are mainly two: (1) To developed a proto-type BCI system that controls three types of movement: left rotation, right rotation, and, going forward; (2) To analyze EEG pattern changes through pre- and post-training conditions. In our BCI system, the EEG signals were derived using bipolar derivation, band-passed in mu and beta frequency bands, and then classified into three brain states. The user trained EEG amplitude control with movement of hands or feet. Using our developed system, a subject participated BCI training by controlling a wheelchair and an avatar in a virtual space. The both types of training were alternately conducted 3 times for each in separate days and each training lasted about 40 minutes. Through whole training, the classification accuracy was increased from 81.5% to 85.5%. Training with wheelchair showed 4% higher accuracy increasing than the training with virtual reality. The result suggests that repetitive control of a BCI-driven wheelchair can provide an effective training for EEG amplitude control.
Keyword (in Japanese) (See Japanese page) 
(in English) mu rhythms / beta rhythms / linear discriminate analysis / virtual reality / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 79, MBE2014-13, pp. 5-8, June 2014.
Paper # MBE2014-13 
Date of Issue 2014-06-06 (MBE) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee MBE  
Conference Date 2014-06-13 - 2014-06-13 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univerisity 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MBE 
Conference Code 2014-06-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Development of a Training Strategy for Electroencephalogram Control Using a Brain-Computer Interface Driven Wheelchair. 
Sub Title (in English)  
Keyword(1) mu rhythms  
Keyword(2) beta rhythms  
Keyword(3) linear discriminate analysis  
Keyword(4) virtual reality  
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Keyword(6)  
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1st Author's Name Yuki Temma  
1st Author's Affiliation Kitami Institute of Technology (Kitami Inst. of Tech.)
2nd Author's Name Shun Matsumoto  
2nd Author's Affiliation Kitami Institute of Technology (Kitami Inst. of Tech.)
3rd Author's Name Kan Matsubara  
3rd Author's Affiliation Kitami Institute of Technology (Kitami Inst. of Tech.)
4th Author's Name Yasunari Hashimoto  
4th Author's Affiliation Kitami Institute of Technology (Kitami Inst. of Tech.)
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Speaker Author-1 
Date Time 2014-06-13 09:25:00 
Presentation Time 25 minutes 
Registration for MBE 
Paper # MBE2014-13 
Volume (vol) vol.114 
Number (no) no.79 
Page pp.5-8 
#Pages 4 
Date of Issue 2014-06-06 (MBE) 

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