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Paper Abstract and Keywords
Presentation 2020-10-09 11:45
Investigation of myoelectric potential features effective for predicting falling of objects due to slippage
Shohei Terada, Masahiro Migita, Masashi Toda (Kumamoto Univ.), Kazuaki Kondo (kyoto Univ.), Junichi Akita (Kanazawa Univ.), Yuichi Nakamura (kyoto Univ.) HIP2020-45
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, sensing technology that appropriately detects a person's intention and state from surface EMG signals generated when trying to move muscles has been used in the development of power assist robots that assist human movements along with the development of machine control technology. Various types of power assisted robots have been developed according to the intention and state of a person, such as a care robot that assists a person in walking and a work robot that assists in lifting a heavy object. Therefore, in this research, we focused on the unstable state due to slippage when holding an object, which is a major obstacle in the movement of a person to hold an object stably. The purpose of this research is to sense the unstable state due to slippage, which is necessary for the development of a power assist robot that supports the holding of objects before dropping. In the experiment, we prepared objects with different slips and measured myoelectric potentials when a person was holding them, and investigated whether there are any features unique to holding a slipping object. It was found that there is a significant difference in the muscle activity of humans and the correlation between the main muscle and the antagonist muscle.
Keyword (in Japanese) (See Japanese page) 
(in English) myelectric signal / muscle activity / wavelet coherence analysis / slip and streaks / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 185, HIP2020-45, pp. 65-69, Oct. 2020.
Paper # HIP2020-45 
Date of Issue 2020-10-01 (HIP) 
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 HIP  
Conference Date 2020-10-08 - 2020-10-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Eye Movement (including Accommodation and Pupil), Spatial Perception (Depth Perception, Motion Perception, etc.), etc. 
Paper Information
Registration To HIP 
Conference Code 2020-10-HIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Investigation of myoelectric potential features effective for predicting falling of objects due to slippage 
Sub Title (in English)  
Keyword(1) myelectric signal  
Keyword(2) muscle activity  
Keyword(3) wavelet coherence analysis  
Keyword(4) slip and streaks  
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1st Author's Name Shohei Terada  
1st Author's Affiliation Kumamoto University (Kumamoto Univ.)
2nd Author's Name Masahiro Migita  
2nd Author's Affiliation Kumamoto University (Kumamoto Univ.)
3rd Author's Name Masashi Toda  
3rd Author's Affiliation Kumamoto University (Kumamoto Univ.)
4th Author's Name Kazuaki Kondo  
4th Author's Affiliation Kyoto University (kyoto Univ.)
5th Author's Name Junichi Akita  
5th Author's Affiliation Kanazawa University (Kanazawa Univ.)
6th Author's Name Yuichi Nakamura  
6th Author's Affiliation Kyoto University (kyoto Univ.)
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Speaker
Date Time 2020-10-09 11:45:00 
Presentation Time 25 
Registration for HIP 
Paper # IEICE-HIP2020-45 
Volume (vol) IEICE-120 
Number (no) no.185 
Page pp.65-69 
#Pages IEICE-5 
Date of Issue IEICE-HIP-2020-10-01 


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