Information: Join today and make your research activities more affordable! Technical workshop participation fees and annual registration fees are available at member rates.
Notice: [Important] Announcement of Changes to Registration Fee Payment and Manuscript Upload Procedures for IEICE Technical Meetings
IEICE Technical Committee Submission System
Conference Paper's Information		 Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2020-11-26 17:20
[Poster Presentation] Accuracy Evaluations of LSTM-based RRI Estimation Method by Using Smartphone Sensors During Exercise
Satomi Shirasaki, Kenji Kanai, Jiro Katto (Waseda Univ.) SeMI2020-29
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, because of aging of the population and increasing medical spending, it is required to shift from the conventional treatment centered medical care to preventive treatment. Therefore, demands for early diagnosis and handy monitoring in daily life is increasing. To address this fact, Internet of Things (IoT) and deep learning get more attention. In this paper, we propose an R-R Interval (RRI) estimation method based on deep learning using smartphone sensors to estimate the RRI without using special medical devices. To construct dataset, we collect ECG, 3-axis acceleration, pressure, illuminance, GPS, and temperature while walking and running by using a smart wear called hitoe and a smartphone. By using the dataset, we adopt a dual stage attention based RNN model to estimate RRI and evaluate the accuracy. The evaluation results conclude that the proposed method can estimate RRI and LF/HF with high accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) RRI estimation / LF/HF estimation / deep learning / IoT / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 261, SeMI2020-29, pp. 57-58, Nov. 2020.
Paper # SeMI2020-29 
Date of Issue 2020-11-19 (SeMI) 
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 SeMI2020-29

Conference Information
Committee SRW SeMI CNR  
Conference Date 2020-11-26 - 2020-11-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) IoT Workshop 
Paper Information
Registration To SeMI 
Conference Code 2020-11-SRW-SeMI-CNR 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Accuracy Evaluations of LSTM-based RRI Estimation Method by Using Smartphone Sensors During Exercise 
Sub Title (in English)  
Keyword(1) RRI estimation  
Keyword(2) LF/HF estimation  
Keyword(3) deep learning  
Keyword(4) IoT  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Satomi Shirasaki  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Kenji Kanai  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Jiro Katto  
3rd Author's Affiliation Waseda University (Waseda Univ.)
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
21st Author's Name  
21st Author's Affiliation ()
22nd Author's Name  
22nd Author's Affiliation ()
23rd Author's Name  
23rd Author's Affiliation ()
24th Author's Name  
24th Author's Affiliation ()
25th Author's Name  
25th Author's Affiliation ()
26th Author's Name / /
26th Author's Affiliation ()
()
27th Author's Name / /
27th Author's Affiliation ()
()
28th Author's Name / /
28th Author's Affiliation ()
()
29th Author's Name / /
29th Author's Affiliation ()
()
30th Author's Name / /
30th Author's Affiliation ()
()
31st Author's Name / /
31st Author's Affiliation ()
()
32nd Author's Name / /
32nd Author's Affiliation ()
()
33rd Author's Name / /
33rd Author's Affiliation ()
()
34th Author's Name / /
34th Author's Affiliation ()
()
35th Author's Name / /
35th Author's Affiliation ()
()
36th Author's Name / /
36th Author's Affiliation ()
()
Speaker Author-1 
Date Time 2020-11-26 17:20:00 
Presentation Time 70 minutes 
Registration for SeMI 
Paper # SeMI2020-29 
Volume (vol) vol.120 
Number (no) no.261 
Page pp.57-58 
#Pages 2 
Date of Issue 2020-11-19 (SeMI) 

[Return to Top Page]

[Return to IEICE Web Page]
The Institute of Electronics, Information and Communication Engineers (IEICE), Japan