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Paper Abstract and Keywords
Presentation 2020-12-15 11:35
A Study on Stress Prediction Model based on Simultaneous Measurement of Environmental and Emotional Data
Koshiro Maeda, Tomoki Hashiguchi, Nobuyoshi Komuro, Keita Hirai (Chiba Univ.) WBS2020-26 ITS2020-22 RCC2020-29
Abstract (in Japanese) (See Japanese page) 
(in English) Emotion estimation technology has attracted attention in terms of work style reform, classroom support, and car driving support. However, conventional techniques for emotion and stress estimation are based on facial expressions, biometric information, and language, and no emotion analysis that does not require such information has yet been proposed. Emotional estimation methods based on images and sounds are fraught with privacy concerns. Biometric-based methods are also subject to the stress problem of biometric sensor attachment. In this study, we develop a system for estimating emotions using only environmental sensors, not images or biometric sensors. In particular, we develop a wireless sensor node that measures environmental information related to human perception, and collect indoor environmental data measured by the developed wireless sensors, as well as emotional data inferred from heartbeat and skin temperature measured by the wearable device, as big data. We then use the collected big data to address the problem of classifying individual emotions. Experimental results show the effectiveness of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) IoT / Society5.0 / Big Data / Wireless Sensor Network / Stress and Emotion Prediction / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 290, WBS2020-26, pp. 103-108, Dec. 2020.
Paper # WBS2020-26 
Date of Issue 2020-12-07 (WBS, ITS, RCC) 
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 WBS2020-26 ITS2020-22 RCC2020-29

Conference Information
Committee ITS WBS RCC  
Conference Date 2020-12-14 - 2020-12-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) ITS Communications, Reliable Communication and Control, Radar and Sensing, etc. 
Paper Information
Registration To WBS 
Conference Code 2020-12-ITS-WBS-RCC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Stress Prediction Model based on Simultaneous Measurement of Environmental and Emotional Data 
Sub Title (in English)  
Keyword(1) IoT  
Keyword(2) Society5.0  
Keyword(3) Big Data  
Keyword(4) Wireless Sensor Network  
Keyword(5) Stress and Emotion Prediction  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Koshiro Maeda  
1st Author's Affiliation Chiba University (Chiba Univ.)
2nd Author's Name Tomoki Hashiguchi  
2nd Author's Affiliation Chiba University (Chiba Univ.)
3rd Author's Name Nobuyoshi Komuro  
3rd Author's Affiliation Chiba University (Chiba Univ.)
4th Author's Name Keita Hirai  
4th Author's Affiliation Chiba University (Chiba Univ.)
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Speaker Author-1 
Date Time 2020-12-15 11:35:00 
Presentation Time 25 minutes 
Registration for WBS 
Paper # WBS2020-26, ITS2020-22, RCC2020-29 
Volume (vol) vol.120 
Number (no) no.290(WBS), no.291(ITS), no.292(RCC) 
Page pp.103-108 
#Pages 6 
Date of Issue 2020-12-07 (WBS, ITS, RCC) 

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