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Paper Abstract and Keywords
Presentation 2019-03-05 16:15
Performance improvement of fNIRS-BCI using generative adversarial networks
Tomoyuki Nagasawa (Nagaoka Univ. of Tech.), Takanori Sato (National Inst. of Tech., Akita Col.), Isao Nambu, Yasuhiro Wada (Nagaoka Univ. of Tech.) NC2018-72
Abstract (in Japanese) (See Japanese page) 
(in English) Since a lengthy functional near-infrared spectroscopy (fNIRS) measurement is uncomfortable for the participant, the number of data that can be acquired is limited. As a result, the training data of the classification model is insufficient; hence, the brain-computer interface (BCI) performance decreases. In this study, to improve the fNIRS-BCI accuracy, we examined an fNIRS data-augmentation method using generative adversarial networks (GANs). When applying the proposed method to the 4-class classification of a left-, right-, or both-handed ball grasping or resting, the accuracy improved after the data augmentation. This result suggests that data augmentation using GANs is useful for improving the fNIRS-BCI performance.
Keyword (in Japanese) (See Japanese page) 
(in English) generative adversarial networks / data augmentation / functional near-infrared spectroscopy / brain-computer interface / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 470, NC2018-72, pp. 151-156, March 2019.
Paper # NC2018-72 
Date of Issue 2019-02-25 (NC) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 NC MBE  
Conference Date 2019-03-04 - 2019-03-06 
Place (in Japanese) (See Japanese page) 
Place (in English) University of Electro Communications 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2019-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance improvement of fNIRS-BCI using generative adversarial networks 
Sub Title (in English)  
Keyword(1) generative adversarial networks  
Keyword(2) data augmentation  
Keyword(3) functional near-infrared spectroscopy  
Keyword(4) brain-computer interface  
1st Author's Name Tomoyuki Nagasawa  
1st Author's Affiliation Nagaoka University of Technology (Nagaoka Univ. of Tech.)
2nd Author's Name Takanori Sato  
2nd Author's Affiliation National Institute of Technology, Akita College (National Inst. of Tech., Akita Col.)
3rd Author's Name Isao Nambu  
3rd Author's Affiliation Nagaoka University of Technology (Nagaoka Univ. of Tech.)
4th Author's Name Yasuhiro Wada  
4th Author's Affiliation Nagaoka University of Technology (Nagaoka Univ. of Tech.)
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Speaker Author-1 
Date Time 2019-03-05 16:15:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2018-72 
Volume (vol) vol.118 
Number (no) no.470 
Page pp.151-156 
Date of Issue 2019-02-25 (NC) 

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