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| Presentation | 2015-08-20 10:20 A Study of High-precision Activity Meter by Microwave Sensor Using Machine Learning Michiyo Hiramoto, Kurato Maeno (OKI)  SIP2015-58 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We have studied a high-precision activity meter without any wearable devices for the elderly who intend to stay at their house all day and to likely be sick gradually. Doppler Microwave sensor can sense from minute moments like a human breathing to body movements. We have applied machine learning technique to build a regression model which relates Doppler signals to METs (metabolic equivalents), then examined its prediction accuracy for daily activities. As a result, the accuracy was similar to an accuracy of a wearable device. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Microwave / METs / Machine Learning / Regression / Activity Meter / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 115, no. 182, SIP2015-58, pp. 41-46, Aug. 2015. | |
| Paper # | SIP2015-58 | |
| Date of Issue | 2015-08-12 (SIP) | |
| 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 | SIP2015-58 |
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| Conference Information | |
| Committee | SIP |
| Conference Date | 2015-08-19 - 2015-08-20 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | National Institute of informatics |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SIP |
| Conference Code | 2015-08-SIP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study of High-precision Activity Meter by Microwave Sensor Using Machine Learning |
| Sub Title (in English) | |
| Keyword(1) | Microwave |
| Keyword(2) | METs |
| Keyword(3) | Machine Learning |
| Keyword(4) | Regression |
| Keyword(5) | Activity Meter |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Michiyo Hiramoto |
| 1st Author's Affiliation | Oki Electric Industry Co., Ltd. (OKI) |
| 2nd Author's Name | Kurato Maeno |
| 2nd Author's Affiliation | Oki Electric Industry Co., Ltd. (OKI) |
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| Speaker | 1 |
| Date Time | 2015-08-20 10:20:00 |
| Presentation Time | 25 |
| Registration for | SIP |
| Paper # | SIP2015-58 |
| Volume (vol) | 115 |
| Number (no) | no.182 |
| Page | pp.41-46 |
| #Pages | 6 |
| Date of Issue | 2015-08-12 (SIP) |
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