Paper Abstract and Keywords |
Presentation |
2012-06-28 10:10
Multi-Class EMG Pattern Classfication using a Selective Desensitization Neural Network with a Half-vs-Half Method Kazumasa Horie (Univ. of Tsukuba), Atsuo Suemitsu (JAIST), Masahiko Morita (Univ. of Tsukuba) NC2012-3 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The real-time classication of human movements by using surface electromyogram (EMG) signals is an important research issue in the development of a new input interface. However, the existing approaches detect irrelevant movements as the target movement, that is, false detection, if the number of the movements to be classied is large. In this research, we propose a new multi-class classication method (half-vs-half method) and apply it to an existing selective desensitization neural network. The result of the evaluation experiment under realistic conditions indicates that the proposed method is rather better than the conventional methods in terms of correct and false detections. The proposed method also does not require more computational time with an increase in the number of classes, complicated parameter setting, and kernel design, which provides a highly practical method for EMG pattern classication. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Selective Desensitization / Neural Network / Electromyogram Signals / Multi-Class Classication / False Detection / / / |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 108, NC2012-3, pp. 13-18, June 2012. |
Paper # |
NC2012-3 |
Date of Issue |
2012-06-21 (NC) |
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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NC2012-3 |
Conference Information |
Committee |
NC IPSJ-BIO |
Conference Date |
2012-06-28 - 2012-06-29 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
OIST, Okinawa |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Machine Learning Approach to Biodata Mining, and General |
Paper Information |
Registration To |
NC |
Conference Code |
2012-06-NC-BIO |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Multi-Class EMG Pattern Classfication using a Selective Desensitization Neural Network with a Half-vs-Half Method |
Sub Title (in English) |
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Keyword(1) |
Selective Desensitization |
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Neural Network |
Keyword(3) |
Electromyogram Signals |
Keyword(4) |
Multi-Class Classication |
Keyword(5) |
False Detection |
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1st Author's Name |
Kazumasa Horie |
1st Author's Affiliation |
University of Tsukuba (Univ. of Tsukuba) |
2nd Author's Name |
Atsuo Suemitsu |
2nd Author's Affiliation |
Japan Advanced Institute of Science and Technology (JAIST) |
3rd Author's Name |
Masahiko Morita |
3rd Author's Affiliation |
University of Tsukuba (Univ. of Tsukuba) |
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Speaker |
Author-1 |
Date Time |
2012-06-28 10:10:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2012-3 |
Volume (vol) |
vol.112 |
Number (no) |
no.108 |
Page |
pp.13-18 |
#Pages |
6 |
Date of Issue |
2012-06-21 (NC) |