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| Presentation | 2018-01-18 11:50 Discrimination of five-finger tapping operation by CNN for fingerless glove-type myoelectric interface Mamoru Hirota, Junki Sato, Ayumu Tsuboi, Masayuki Yokoyama, Masao Yanagisawa (Waseda Univ)  PRMU2017-125 MVE2017-46 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In recent years, research on input interfaces that anticipate the spread of VR devices to various fields is widely conducted. Therefore, detailed tracking is required more than conventional motion tracking. In this paper, we aim to develop a fingerless glove type EMG interface with dry electrodes on the back of hand, to identify the tapping motion of 5 fingers as the movement of fingers, and use a convolution neural network for the acquired EMG information. We introduced two types of the classifier, and verified the accuracy of finger action identification. Experiments were conducted on eleven subjects and the obtained electromyogram information was identified by each method. As a result, the average accuracy was 88.61% for identification in linear discriminant analysis and 87.98% for average convolution neural network became. We discussed the cause of this result and future prospects. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | EMG / gesture recognition / interface / CNN / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 392, MVE2017-46, pp. 111-116, Jan. 2018. | |
| Paper # | MVE2017-46 | |
| Date of Issue | 2018-01-11 (PRMU, MVE) | |
| 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) | |
| Download PDF | PRMU2017-125 MVE2017-46 |
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| Conference Information | |
| Committee | PRMU MVE IPSJ-CVIM |
| Conference Date | 2018-01-18 - 2018-01-19 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | MVE |
| Conference Code | 2018-01-PRMU-MVE-CVIM |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Discrimination of five-finger tapping operation by CNN for fingerless glove-type myoelectric interface |
| Sub Title (in English) | |
| Keyword(1) | EMG |
| Keyword(2) | gesture recognition |
| Keyword(3) | interface |
| Keyword(4) | CNN |
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| 1st Author's Name | Mamoru Hirota |
| 1st Author's Affiliation | Waseda University (Waseda Univ) |
| 2nd Author's Name | Junki Sato |
| 2nd Author's Affiliation | Waseda University (Waseda Univ) |
| 3rd Author's Name | Ayumu Tsuboi |
| 3rd Author's Affiliation | Waseda University (Waseda Univ) |
| 4th Author's Name | Masayuki Yokoyama |
| 4th Author's Affiliation | Waseda University (Waseda Univ) |
| 5th Author's Name | Masao Yanagisawa |
| 5th Author's Affiliation | Waseda University (Waseda Univ) |
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| Speaker | Author-1 |
| Date Time | 2018-01-18 11:50:00 |
| Presentation Time | 25 minutes |
| Registration for | MVE |
| Paper # | PRMU2017-125, MVE2017-46 |
| Volume (vol) | vol.117 |
| Number (no) | no.391(PRMU), no.392(MVE) |
| Page | pp.111-116 |
| #Pages | 6 |
| Date of Issue | 2018-01-11 (PRMU, MVE) |
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