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| Paper Abstract and Keywords | ||
| Presentation | 2022-07-07 14:55 3s2sub: A Proposal of Data Segmentation Scheme for Fall Detection by Smartphone Built-in Accelerator Pengyu Guo, Masaya Nakayama (Uni.Tokyo)  LOIS2022-7 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | A Fall is defined as an event which results in a person coming to rest inadvertently on the ground or floor or other lower level. While threatening people's lives, it also brings huge economic costs. In this work, data segmentation scheme called 3s2sub is proposed, which is to detect fall with smartphone built-in accelerator. The approach is tested with a public dataset – UniMiB SHAR. The accuracy achieved by KNN and SVM are about 98% in 30-fold evaluation. And Macro Average accuracy are about 97% and 98% in 30-fold evaluation. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Activity Recognition / Fall Detection / Smartphone built-in Sensor / Accelerometer / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 97, LOIS2022-7, pp. 18-23, July 2022. | |
| Paper # | LOIS2022-7 | |
| Date of Issue | 2022-06-30 (LOIS) | |
| 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 | LOIS2022-7 |
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| Conference Information | |
| Committee | LOIS IPSJ-DC |
| Conference Date | 2022-07-07 - 2022-07-07 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | LOIS |
| Conference Code | 2022-07-LOIS-DC |
| Language | English (Japanese title is available) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | 3s2sub: A Proposal of Data Segmentation Scheme for Fall Detection by Smartphone Built-in Accelerator |
| Sub Title (in English) | |
| Keyword(1) | Activity Recognition |
| Keyword(2) | Fall Detection |
| Keyword(3) | Smartphone built-in Sensor |
| Keyword(4) | Accelerometer |
| Keyword(5) | |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Pengyu Guo |
| 1st Author's Affiliation | The University of Tokyo (Uni.Tokyo) |
| 2nd Author's Name | Masaya Nakayama |
| 2nd Author's Affiliation | The University of Tokyo (Uni.Tokyo) |
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| Speaker | Author-1 |
| Date Time | 2022-07-07 14:55:00 |
| Presentation Time | 25 minutes |
| Registration for | LOIS |
| Paper # | LOIS2022-7 |
| Volume (vol) | vol.122 |
| Number (no) | no.97 |
| Page | pp.18-23 |
| #Pages | 6 |
| Date of Issue | 2022-06-30 (LOIS) |
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