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Paper Abstract and Keywords
Presentation 2026-03-17 13:55
A Consideration on High-accuracy Arm Motion Prediction Using Bio-signals and LSTM for Communication Delay Compensation
Yurika Machida, Wataru Kameyama (Waseda Univ.) CQ2025-116
Abstract (in Japanese) (See Japanese page) 
(in English) This paper examines a method for predicting arm motion 0.5-seconds ahead using bio-signals and a Long Short-Term Memory (LSTM) model, aiming to compensate for communication delays in teleoperated robotic arm systems. Previous studies have demonstrated the effectiveness of surface electromyography (sEMG) for one-dimensional (1D) and two-dimensional (2D) motion prediction, however, prediction accuracy often varies across subjects. In this paper, to improve robustness in 2D coordinate prediction, min-max normalization is applied, and the learning sequence length is optimized. Several analysis methods are compared under these conditions. In addition, electroencephalography (EEG) is evaluated alongside sEMG for both 1D and 2D motion prediction. The results show that, for 2D motion, a learning sequence length of 75 combined with a velocity-based prediction approach achieves stable and high accuracy across subjects. For 1D motion prediction, using EEG alone yields a mean coefficient of determination of 0.916. These findings suggest that the proposed method is effective for multi-dimensional motion prediction and has potential for real-time teleoperation with communication delay compensation.
Keyword (in Japanese) (See Japanese page) 
(in English) Arm Motion Prediction / Machine Learning / Communication Delays / Electromyography / Electroencephalography / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 409, CQ2025-116, pp. 85-90, March 2026.
Paper # CQ2025-116 
Date of Issue 2026-03-09 (CQ) 
ISSN 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 CQ2025-116

Conference Information
Committee CQ MVE IMQ IE  
Conference Date 2026-03-16 - 2026-03-18 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa-Sangyoushien-Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CQ 
Conference Code 2026-03-CQ-MVE-IMQ-IE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Consideration on High-accuracy Arm Motion Prediction Using Bio-signals and LSTM for Communication Delay Compensation 
Sub Title (in English)  
Keyword(1) Arm Motion Prediction  
Keyword(2) Machine Learning  
Keyword(3) Communication Delays  
Keyword(4) Electromyography  
Keyword(5) Electroencephalography  
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1st Author's Name Yurika Machida  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Wataru Kameyama  
2nd Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2026-03-17 13:55:00 
Presentation Time 20 minutes 
Registration for CQ 
Paper # CQ2025-116 
Volume (vol) vol.125 
Number (no) no.409 
Page pp.85-90 
#Pages 6 
Date of Issue 2026-03-09 (CQ) 

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