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Proceedings Paper

Feasibility study and preliminary design of load-assisting clothes for lumbar protection inspired by human musculoskeletal systems
Author(s): Riho Hashimoto; Arata Masuda; Hao Chen; Sou Kobayashi
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Paper Abstract

The purpose of this paper is to develop load assisting clothes for caregivers. Low back pain is one of the most major reasons for caregivers to leave their jobs. In this study, load assisting clothes which reduce the risks of low back pain of caregivers are designed and manufactured, targeting at the use in small care-houses and family caregiving. The load assisting clothes should have two functions. One is to reduce the compressive load acting on the lumbar spine as well as the tensile load on the lumbar muscles by providing an appropriate assisting force. The other is not to interfere with wearers’ motion. The proposed approach in this study is to put elastic compressive members and tensioner belts integrated in the garment to provide the assisting forces without hindering natural movement and comfortable feeling. We study human musculoskeletal systems in the lumbar part, and consider to construct a parallel reinforcement of it on the body surface by embedding passive support structures. The arrangement of those elements is determined based on the study of the principal strain directions and the non-extension directions of the body surface to manage the appropriate assisting force without spoiling the mobility. The effectiveness of the proposed support principle is verified through experimental studies.

Paper Details

Date Published: 22 April 2016
PDF: 11 pages
Proc. SPIE 9797, Bioinspiration, Biomimetics, and Bioreplication 2016, 979712 (22 April 2016); doi: 10.1117/12.2219526
Show Author Affiliations
Riho Hashimoto, Kyoto Institute of Technology (Japan)
Arata Masuda, Kyoto Institute of Technology (Japan)
Hao Chen, Kyoto Institute of Technology (Japan)
Sou Kobayashi, Kyoto Institute of Technology (Japan)


Published in SPIE Proceedings Vol. 9797:
Bioinspiration, Biomimetics, and Bioreplication 2016
Raúl J. Martín-Palma; Akhlesh Lakhtakia; Mato Knez, Editor(s)

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