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| 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 |
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| 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. |
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| 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 | |
| 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 | MICT2021-101 |
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| 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 |
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| 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 |
| #Pages | 6 |
| Date of Issue | 2022-02-25 (MICT) |
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