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Paper Abstract and Keywords
Presentation 2007-06-22 09:20
A Brain Computer Interface Based on FFT and Multilayer Neural Network -- Feature Extraction and Generalization --
Yasuaki Kaneda, Kenji Nakayama, Akihiro Hirano (Kanazawa Univ.) CAS2007-19 VLD2007-35 SIP2007-49
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, a multilayer neural network is applied to 'Brain Computer Interface' (BCI), which is one of hopeful interface technologies between humans and machines. Amplitude of the FFT of the brain waves are used for the input data. Several techniques have been introduced for pre-processing the brain waves. They include segmentation along the time axis for fast response, nonlinear normalization to emphasize important information, averaging samples of the brain waves to suppress noise effects, reduction in the number of the samples to realize a small size network, and so on. In this paper, two kinds of generalization techniques, including adding small random noises to the input data and decaying connection weight magnitude, are applied. Their usefulness are analyzed and compared based on correct and error classifications. Simulation is carried out by using the brain waves, which are available from the web site of Colorado State University. The number of mental tasks is five. Some data sets are used for training the multilayer neural network, and the remaining data sets are used for testing. In our previous work, classification accuracy of 64%-74% for the test data have been achieved. In this paper, by applying the generalization techniques, the accuracy can be improved up to 80%-88%.
Keyword (in Japanese) (See Japanese page) 
(in English) Brain computer interface / Mental task / Multilayer neural network / Feature extraction / Generalization / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 105, SIP2007-49, pp. 1-6, June 2007.
Paper # SIP2007-49 
Date of Issue 2007-06-15 (CAS, VLD, SIP) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
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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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF CAS2007-19 VLD2007-35 SIP2007-49

Conference Information
Committee CAS SIP VLD  
Conference Date 2007-06-21 - 2007-06-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Tokai Univ. (Sapporo) 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SIP 
Conference Code 2007-06-CAS-SIP-VLD 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Brain Computer Interface Based on FFT and Multilayer Neural Network 
Sub Title (in English) Feature Extraction and Generalization 
Keyword(1) Brain computer interface  
Keyword(2) Mental task  
Keyword(3) Multilayer neural network  
Keyword(4) Feature extraction  
Keyword(5) Generalization  
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1st Author's Name Yasuaki Kaneda  
1st Author's Affiliation Kanazawa University (Kanazawa Univ.)
2nd Author's Name Kenji Nakayama  
2nd Author's Affiliation Kanazawa University (Kanazawa Univ.)
3rd Author's Name Akihiro Hirano  
3rd Author's Affiliation Kanazawa University (Kanazawa Univ.)
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Speaker
Date Time 2007-06-22 09:20:00 
Presentation Time 20 
Registration for SIP 
Paper # IEICE-CAS2007-19,IEICE-VLD2007-35,IEICE-SIP2007-49 
Volume (vol) IEICE-107 
Number (no) no.101(CAS), no.103(VLD), no.105(SIP) 
Page pp.1-6 
#Pages IEICE-6 
Date of Issue IEICE-CAS-2007-06-15,IEICE-VLD-2007-06-15,IEICE-SIP-2007-06-15 


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