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| Presentation | 2020-03-05 11:35 Predicting Leg Muscle Strength and Imbalance using Mocap Data for Elderly People Simon Schlegl, Xueting Wang, Toshihiko Yamasaki (UT), Mingchuan Zhou, Alois Knoll (TUM), Yoshikuni Sato, Takahiro Hiyama (Panasonic), Yasuko Yoshinaka, Misaka Kimura (KUAS)  IMQ2019-45 IE2019-127 MVE2019-66 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | With progressing age certain health risks such as falling become both more likely and more life-threatening. One of the indicators to predict the risk of falling is leg muscle strength, which is traditionally measured by a trained physician. However, for continuous risk assessment, an approach that does not require any special tests is preferable. In order to pave the way for a purely video based analysis we analyzed the correlation between walking patterns that can be extracted from video material and leg muscle strength as well as imbalance, as those parameters are known to be directly connected to falls. We show that there are several parameters such as stride time or length that are correlated to leg muscle strength and thus might be suitable for risk assessment. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | muscle strength prediction / motion capture / / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 457, MVE2019-66, pp. 151-156, March 2020. | |
| Paper # | MVE2019-66 | |
| Date of Issue | 2020-02-27 (IMQ, IE, MVE) | |
| 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 | IMQ2019-45 IE2019-127 MVE2019-66 |
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| Conference Information | |
| Committee | IE IMQ MVE CQ |
| Conference Date | 2020-03-05 - 2020-03-06 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyushu Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | MVE |
| Conference Code | 2020-03-IE-IMQ-MVE-CQ |
| Language | English (Japanese title is available) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Predicting Leg Muscle Strength and Imbalance using Mocap Data for Elderly People |
| Sub Title (in English) | |
| Keyword(1) | muscle strength prediction |
| Keyword(2) | motion capture |
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| 1st Author's Name | Simon Schlegl |
| 1st Author's Affiliation | The University of Tokyo (UT) |
| 2nd Author's Name | Xueting Wang |
| 2nd Author's Affiliation | The University of Tokyo (UT) |
| 3rd Author's Name | Toshihiko Yamasaki |
| 3rd Author's Affiliation | The University of Tokyo (UT) |
| 4th Author's Name | Mingchuan Zhou |
| 4th Author's Affiliation | Technical University of Munich (TUM) |
| 5th Author's Name | Alois Knoll |
| 5th Author's Affiliation | Technical University of Munich (TUM) |
| 6th Author's Name | Yoshikuni Sato |
| 6th Author's Affiliation | Panasonic Corporation (Panasonic) |
| 7th Author's Name | Takahiro Hiyama |
| 7th Author's Affiliation | Panasonic Corporation (Panasonic) |
| 8th Author's Name | Yasuko Yoshinaka |
| 8th Author's Affiliation | Kyoto University of Advanced Science (KUAS) |
| 9th Author's Name | Misaka Kimura |
| 9th Author's Affiliation | Kyoto University of Advanced Science (KUAS) |
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| Speaker | Author-1 |
| Date Time | 2020-03-05 11:35:00 |
| Presentation Time | 25 minutes |
| Registration for | MVE |
| Paper # | IMQ2019-45, IE2019-127, MVE2019-66 |
| Volume (vol) | vol.119 |
| Number (no) | no.454(IMQ), no.456(IE), no.457(MVE) |
| Page | pp.151-156 |
| #Pages | 6 |
| Date of Issue | 2020-02-27 (IMQ, IE, MVE) |
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