Hypogravity modeling of upper extremities: an investigation of manual handling in the workplace.

joint angles markerless motion capture motion analysis reduced gravity workplace design

Journal

Frontiers in physiology
ISSN: 1664-042X
Titre abrégé: Front Physiol
Pays: Switzerland
ID NLM: 101549006

Informations de publication

Date de publication:
2023
Historique:
received: 31 03 2023
accepted: 29 08 2023
medline: 19 10 2023
pubmed: 19 10 2023
entrez: 19 10 2023
Statut: epublish

Résumé

Experiments on the lower limbs are the only approaches being used to study how hypogravity (HG) (0 < g < 1, e.g., Moon: 1/6 g, Mars: 3/8 g) affects human movement. The goal of this study was to expand this field experimentally by investigating the effect of HG on the upper extremities during one-handed manual handling tasks in a sitting posture: static weight holding with an outstretched arm, and slow repetitive weight lifting and lowering motions. The hypothesis was that while completing static and dynamic tasks with elements of repetition in HG, the upper body's tilt (angle regarding the vertical axis) would change differently from Earth's gravity. Specifically, upper arm and spine angles, joint torques, and forces were investigated. Twenty-four healthy participants aged 33.6 ± 8.2 years were involved in the trial. Joint angles were examined using vision-based 3D motion analysis. According to this investigation, there is a correlation between a body tilting backward and a gravity level reduction (

Identifiants

pubmed: 37854467
doi: 10.3389/fphys.2023.1198162
pii: 1198162
pmc: PMC10580979
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1198162

Informations de copyright

Copyright © 2023 Maillard.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Tatiana Maillard (T)

Space Innovation, Doctoral Program in Civil and Environmental Engineering, Swiss Federal Institute of Technology in Lausanne, Lausanne, Switzerland.

Classifications MeSH