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| Presentation | 2018-01-27 14:25 Evaluation of Generalization Performance of Finger Motion Classifier with input of surface EMG signal of hand intrinsic muscles Junki Sato, Ayumu Tsuboi, Hirota Mamoru, Masayuki Yokoyama, Masao Yanagisawa (Waseda Univ.)  MBE2017-78 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | The hand and finger motions are achieved by the cooperative action of the forearm which includes extrinsic muscles, and the fingers which include intrinsic muscles. More precise recognition is possible by using surface electromyography(sEMG) of the intrinsic muscle in delicate finger motion analysis. We aimed to realize the development of a new user interface based on EMG information of the fingers, and we developed a wearable glove type device using dry electrodes. In the assumption of usage as interface, it is inconvenient to recalibrate for each user. Thus, it will be necessary to select features which enable the classifier to accurately recognize unknown user's myoelectric signal and to select classifier according to the amount. With this device, we measured the myoelectric signal of eleven subjects during the tapping operation, and examined the recognition of tapping motion using six features and multilayer perceptron between different subjects. The result was the 92.0% accuracy at 1kHz sampling frequency and 89.8% at 100Hz. It suggested the high generalization performance and usefulness as an EMG based interface. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | EMG / hand / finger / intrinsic muscles / gesture recognition / interface / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 416, MBE2017-78, pp. 65-70, Jan. 2018. | |
| Paper # | MBE2017-78 | |
| Date of Issue | 2018-01-19 (MBE) | |
| 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 | MBE2017-78 |
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| Conference Information | |
| Committee | MBE NC NLP |
| Conference Date | 2018-01-26 - 2018-01-27 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyushu Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | ME, generalImplementation of Neuro Computing,Analysis and Modeling of Human Science, |
| Paper Information | |
| Registration To | MBE |
| Conference Code | 2018-01-MBE-NC-NLP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Evaluation of Generalization Performance of Finger Motion Classifier with input of surface EMG signal of hand intrinsic muscles |
| Sub Title (in English) | |
| Keyword(1) | EMG |
| Keyword(2) | hand |
| Keyword(3) | finger |
| Keyword(4) | intrinsic muscles |
| Keyword(5) | gesture recognition |
| Keyword(6) | interface |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Junki Sato |
| 1st Author's Affiliation | Waseda University (Waseda Univ.) |
| 2nd Author's Name | Ayumu Tsuboi |
| 2nd Author's Affiliation | Waseda University (Waseda Univ.) |
| 3rd Author's Name | Hirota Mamoru |
| 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 | 2018-01-27 14:25:00 |
| Presentation Time | 25 minutes |
| Registration for | MBE |
| Paper # | MBE2017-78 |
| Volume (vol) | vol.117 |
| Number (no) | no.416 |
| Page | pp.65-70 |
| #Pages | 6 |
| Date of Issue | 2018-01-19 (MBE) |
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