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Paper Abstract and Keywords
Presentation 2023-03-15 10:05
Real-time stress detection using Yuragi learning by multimodal integration of living-body information
Risa Yoshida, Yuichi Ohsita, Masayuki Murata (Osaka Univ.) MBE2022-68
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, psychological fatigue based on the working environment and mental strain has become an issue. Therefore, we believe that real-time detection of stress using multiple living-body information that can be acquired from wearable sensors can promote rest. However, such living-body information measured by wearable devices contains noise. In addition individual differences exist in such living-body information. In this paper, we propose a real-time stress detection method that can handle noise included in the monitored information and the individual differences. Our approach is based on ”Yuragi learning” and multimodal integration. Also, our methods select the information for each person and exclude the information that cannot distinguish the stress state. In this paper, we demonstrate that our method detect stress states accurately through experiments.The results show that our method can detect stress accurately, while the methods without selecting modalities and without avoiding using results with low confidence cause false negatives and false positives.
Keyword (in Japanese) (See Japanese page) 
(in English) Living-body information / Real-time stress detection / Yuragi learning / BAM (Bayesian Attractor Model) / Multimodal integration / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 424, MBE2022-68, pp. 49-54, March 2023.
Paper # MBE2022-68 
Date of Issue 2023-03-06 (MBE) 
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 MBE2022-68

Conference Information
Committee NC MBE  
Conference Date 2023-03-13 - 2023-03-15 
Place (in Japanese) (See Japanese page) 
Place (in English) The Univ. of Electro-Communications 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Brain architecture, General 
Paper Information
Registration To MBE 
Conference Code 2023-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Real-time stress detection using Yuragi learning by multimodal integration of living-body information 
Sub Title (in English)  
Keyword(1) Living-body information  
Keyword(2) Real-time stress detection  
Keyword(3) Yuragi learning  
Keyword(4) BAM (Bayesian Attractor Model)  
Keyword(5) Multimodal integration  
Keyword(6)  
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1st Author's Name Risa Yoshida  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Yuichi Ohsita  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Masayuki Murata  
3rd Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2023-03-15 10:05:00 
Presentation Time 25 minutes 
Registration for MBE 
Paper # MBE2022-68 
Volume (vol) vol.122 
Number (no) no.424 
Page pp.49-54 
#Pages 6 
Date of Issue 2023-03-06 (MBE) 

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