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Paper Abstract and Keywords
Presentation 2008-01-15 16:10
Feature Analysis of Auditory Evoked Potentials by Statistical Discrimination
Yasuyuki Inoue (TUT), Akitoshi Ogawa (RIKEN), Kouta Arai, Hidehiko Matsumoto (Sakushin Gakuin Univ.), Atsuhito Toyomaki (Hokkaido Univ.), Hiroshige Takeichi (RIKEN), Takashi Omori, Sachiko Koyama (Hokkaido Univ.), Takashi Morotomi (Sakushin Gakuin Univ.), Michiteru Kitazaki (TUT) NC2007-94
Abstract (in Japanese) (See Japanese page) 
(in English) To estimate the input stimulus from observer's evoked brain potentials (ERPs), we have developed a classification technique using Principal Component Analysis (PCA) and Naive Bayes method. Our method does not require a priori knowledge about stimuli, and it is easy to apply because of its simplicity and stability. In this study, we applied the technique to classify auditory ERPs that were elicited by temporal gaps embedded in a continuous pure tone. The classifier that was constructed from ERP data elicited by long gap showed higher correct rate than that of short gap. Accuracy was significantly higher than the chance level, indicating that statistical discrimination of temporal gap stimuli was successful and would be available for quantitative feature analysis method of ERPs.
Keyword (in Japanese) (See Japanese page) 
(in English) Auditory Evoked Brain Potentials / Principal Component Analysis / Naive Bayes Method / / / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 413, NC2007-94, pp. 43-48, Jan. 2008.
Paper # NC2007-94 
Date of Issue 2008-01-08 (NC) 
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. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee NC  
Conference Date 2008-01-15 - 2008-01-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Centennial Hall, Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Machine Learning, etc. 
Paper Information
Registration To NC 
Conference Code 2008-01-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Feature Analysis of Auditory Evoked Potentials by Statistical Discrimination 
Sub Title (in English)  
Keyword(1) Auditory Evoked Brain Potentials  
Keyword(2) Principal Component Analysis  
Keyword(3) Naive Bayes Method  
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1st Author's Name Yasuyuki Inoue  
1st Author's Affiliation Toyohashi University of Technology (TUT)
2nd Author's Name Akitoshi Ogawa  
2nd Author's Affiliation RIKEN (RIKEN)
3rd Author's Name Kouta Arai  
3rd Author's Affiliation Sakushin Gakuin University (Sakushin Gakuin Univ.)
4th Author's Name Hidehiko Matsumoto  
4th Author's Affiliation Sakushin Gakuin University (Sakushin Gakuin Univ.)
5th Author's Name Atsuhito Toyomaki  
5th Author's Affiliation HokkaidoUniversity (Hokkaido Univ.)
6th Author's Name Hiroshige Takeichi  
6th Author's Affiliation RIKEN (RIKEN)
7th Author's Name Takashi Omori  
7th Author's Affiliation HokkaidoUniversity (Hokkaido Univ.)
8th Author's Name Sachiko Koyama  
8th Author's Affiliation HokkaidoUniversity (Hokkaido Univ.)
9th Author's Name Takashi Morotomi  
9th Author's Affiliation Sakushin Gakuin University (Sakushin Gakuin Univ.)
10th Author's Name Michiteru Kitazaki  
10th Author's Affiliation Toyohashi University of Technology (TUT)
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Speaker Author-1 
Date Time 2008-01-15 16:10:00 
Presentation Time 20 minutes 
Registration for NC 
Paper # NC2007-94 
Volume (vol) vol.107 
Number (no) no.413 
Page pp.43-48 
#Pages
Date of Issue 2008-01-08 (NC) 


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