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| Presentation | 2020-03-05 09:40 FMCW Radar-based Anomaly Detection in Toilet by Spectrogram Analysis with LSTM Takabatake Wataru, Mondher Bouazizi, Kohei Yamamoto, Tomoaki Ohtsuki (Keio Univ.), Yohei Shibata, Atushi Nagate ()  RCS2019-351 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | With the increase in the population of elderly, elderly monitoring techniques are receiving more and more attention all over the world. In particular, it is highly demanded to develop the system that detects accidents in a toilet, since such accidents are likely to get worse due to late detection. In this report, we propose an FMCW(Frequency Modulated Continuous Wave) radar-based anomaly detection method in toilet. In the proposed method, at rst, time-series data of the statistics such as mean, standard deviation, skewness, and kurtosis for each time and power changes for each distance. The data for about 9 seconds are classi ed into a faint or a non-faint by LSTM (Long Short Term Memory). LSTM, the one of the deep learning methods needs more data and more various data. Though, collecting the data is not easy. Thus, we make new data from the existing data by GAN(Generative Adversarial Network). In the experiments, we observed 4 fainting behaviors: (i) stooping on the seat, (ii) leaning on the backrest, (iii) leaning on the sidewall on the seat, and (iv) lying on the floor after the fall. Also we observed the following normal behaviors such as sitting still after the button operation and sitting down. We conducted the experiments with 13 people. As a result, we con rmed that our proposed method detected the fainting behaviors with the Accuray of 0.83. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | FMCW radar / Anomaly detection / Toilet / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 448, RCS2019-351, pp. 165-170, March 2020. | |
| Paper # | RCS2019-351 | |
| Date of Issue | 2020-02-26 (RCS) | |
| 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 | RCS2019-351 |
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| Conference Information | |
| Committee | RCS SR SRW |
| Conference Date | 2020-03-04 - 2020-03-06 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tokyo Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Mobile Communication Workshop |
| Paper Information | |
| Registration To | RCS |
| Conference Code | 2020-03-RCS-SR-SRW |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | FMCW Radar-based Anomaly Detection in Toilet by Spectrogram Analysis with LSTM |
| Sub Title (in English) | |
| Keyword(1) | FMCW radar |
| Keyword(2) | Anomaly detection |
| Keyword(3) | Toilet |
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| 1st Author's Name | Takabatake Wataru |
| 1st Author's Affiliation | Keio University (Keio Univ.) |
| 2nd Author's Name | Mondher Bouazizi |
| 2nd Author's Affiliation | Keio University (Keio Univ.) |
| 3rd Author's Name | Kohei Yamamoto |
| 3rd Author's Affiliation | Keio University (Keio Univ.) |
| 4th Author's Name | Tomoaki Ohtsuki |
| 4th Author's Affiliation | Keio University (Keio Univ.) |
| 5th Author's Name | Yohei Shibata |
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| 6th Author's Name | Atushi Nagate |
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| Speaker | Author-1 |
| Date Time | 2020-03-05 09:40:00 |
| Presentation Time | 20 minutes |
| Registration for | RCS |
| Paper # | RCS2019-351 |
| Volume (vol) | vol.119 |
| Number (no) | no.448 |
| Page | pp.165-170 |
| #Pages | 6 |
| Date of Issue | 2020-02-26 (RCS) |
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