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Paper Abstract and Keywords
Presentation 2017-11-17 15:25
Examination of Methods for Detecting Change of Indoor Walking Patterns Using Sparse Position Information
Kazuki Takagi, Ryoichi Shinkuma (Kyoto Univ.), Hideyuki Shimizu, Hisashi Sakamoto (NEC Solution Innovators) MoNA2017-20
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, the Internet-of-Things (IoT) technology has been attracting a lot of attention as a solution that detects health risk of elderly people by monitoring and analyzing their daily behaviors.
Using cameras or wearable devices is a typical approach to track people's behaviors in their house.
However, these devices have drawbacks: people feel uncomfortable from the privacy aspect if they are always watched by cameras; people feel annoyed if they are required to always carry wearable devices.
Therefore, vibration sensors or human sensors could be more appropriate for behavior monitoring in a indoor private environment like houses though they might be able to collect discrete and sparse data.
In this report, we propose a method that detects changes in behavior patterns of elderly people who live alone by using sparse position information from sensors.
Our method successfully models usual behavior patters by representing movement patterns between multiple sensors of people as a network graph.
Then, our method detects changes in people's behaviors by scoring the similarity of network graphs between the measured behavior pattern and the usual behavior patters.This paper validates our method through simulation evaluation.
Keyword (in Japanese) (See Japanese page) 
(in English) Anomaly Detection / Elderly Care / Position Tracking / Network Graph / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 308, MoNA2017-20, pp. 31-34, Nov. 2017.
Paper # MoNA2017-20 
Date of Issue 2017-11-09 (MoNA) 
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 MoNA2017-20

Conference Information
Committee CNR IN MoNA  
Conference Date 2017-11-16 - 2017-11-17 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MoNA 
Conference Code 2017-11-CNR-IN-MoNA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Examination of Methods for Detecting Change of Indoor Walking Patterns Using Sparse Position Information 
Sub Title (in English)  
Keyword(1) Anomaly Detection  
Keyword(2) Elderly Care  
Keyword(3) Position Tracking  
Keyword(4) Network Graph  
Keyword(5)  
Keyword(6)  
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1st Author's Name Kazuki Takagi  
1st Author's Affiliation Kyoto University (Kyoto Univ.)
2nd Author's Name Ryoichi Shinkuma  
2nd Author's Affiliation Kyoto University (Kyoto Univ.)
3rd Author's Name Hideyuki Shimizu  
3rd Author's Affiliation NEC Solution Innovators, Ltd. (NEC Solution Innovators)
4th Author's Name Hisashi Sakamoto  
4th Author's Affiliation NEC Solution Innovators, Ltd. (NEC Solution Innovators)
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Speaker Author-1 
Date Time 2017-11-17 15:25:00 
Presentation Time 25 minutes 
Registration for MoNA 
Paper # MoNA2017-20 
Volume (vol) vol.117 
Number (no) no.308 
Page pp.31-34 
#Pages 4 
Date of Issue 2017-11-09 (MoNA) 

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