| Title: | GS6-1 Development of Smartphone Application for Calculating the Low Back Pain Risk |
|---|---|
| Publication: | ICAROB2024 |
| Volume: | 29 |
| Pages: | 1038-1041 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2024.GS6-1 |
| Author(s): | Seigo Imura, Praveen Gunaratne, Hiroki Tamura |
| Publication Date: | February 22, 2024 |
| Keywords: | Lumbar burden estimation, smartphone application, voice recognition |
| Abstract: | This study primarily relies on a smartphone application, developed within our research institute known as Yo-bukun, for the real-time estimation of lumbar burden. The Yo-bukun is capable of estimating the lumbar burden of a subject (the user) by placing an app. installed smartphone in the subject's chest pocket, while the subject is lifting/ relocating an object. The subject's movements are assessed through sensors embedded in the smartphone and certain aspects of their physical information initially fed into the app. are used in the estimation formula for determining lumbar burden. In the current scenario, Yo-bukun lacks the capability to ascertain whether the user is holding an object or not; consequently, it can only estimate the lumbar burden for limited cases of a subject holding an object. To address such limitations, the proposed system integrates voice recognition to facilitate lumbar burden estimation, considering the presence or absence of an object. Further, it was incorporated with the capability to recalculate lumbar burden after measurements, enabling prospective studies. |
| PDF File: | https://alife-robotics.co.jp/members2024/icarob/data/html/data/GS/GS6-1.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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