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Paper Abstract and Keywords
Presentation 2022-03-04 09:05
A Study on Non-contact Blood Pressure Estimation Method based on Subject Classification by Machine Learning
Shuzo Ishizaka, Kohei Yamamoto, Tomoaki Ohtsuki (Keio Univ.) MICT2021-101
Abstract (in Japanese) (See Japanese page) 
(in English) Non-contact Blood Pressure (BP) measurement is receiving a lot of interest for BP measurement on a daily basis.
To realize non-contact BP measurement, the use of a Doppler radar has been investigated.
A Doppler radar can detect the pulse wave caused by chest displacement due to heartbeat.
BP can be estimated by constructing a BP estimation model using features that correlate with BP obtained from the pulse wave.
However, compared to the case of modeling for each subject, the accuracy of BP estimation deteriorates significantly when modeling with multiple subjects other than the target subject.
In this report, to improve the accuracy of BP estimation when modeling with multiple subjects, we proposed a non-contact BP estimation method using a Doppler radar based on subject classification.
In the proposed method, subjects are classified by Principal Component Analysis (PCA) and hierarchical clustering.
A BP estimation model that inputs the features that correlate with BP and outputs Systolic BP (Systolic Blood Pressure) is constructed for each classified cluster.
The experimental results showed that when modeling with multiple subjects other than a testing subject, the proposed method achieved high the BP estimation accuracy, compared to the method without subject classification.
Keyword (in Japanese) (See Japanese page) 
(in English) Doppler radar / Non-contact blood pressure estimation / Machine learning / Health care / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 404, MICT2021-101, pp. 1-6, March 2022.
Paper # MICT2021-101 
Date of Issue 2022-02-25 (MICT) 
ISSN Online edition: ISSN 2432-6380
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 MICT2021-101

Conference Information
Committee MICT EMCJ  
Conference Date 2022-03-04 - 2022-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Healthcare and Medical Information Communication Technologies, EMC, etc 
Paper Information
Registration To MICT 
Conference Code 2022-03-MICT-EMCJ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Non-contact Blood Pressure Estimation Method based on Subject Classification by Machine Learning 
Sub Title (in English)  
Keyword(1) Doppler radar  
Keyword(2) Non-contact blood pressure estimation  
Keyword(3) Machine learning  
Keyword(4) Health care  
1st Author's Name Shuzo Ishizaka  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Kohei Yamamoto  
2nd Author's Affiliation Keio University (Keio Univ.)
3rd Author's Name Tomoaki Ohtsuki  
3rd Author's Affiliation Keio University (Keio Univ.)
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Speaker Author-1 
Date Time 2022-03-04 09:05:00 
Presentation Time 20 minutes 
Registration for MICT 
Paper # MICT2021-101 
Volume (vol) vol.121 
Number (no) no.404 
Page pp.1-6 
Date of Issue 2022-02-25 (MICT) 

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