Upper-Limb Isometric Force Feasible Set: Evaluation of Joint Torque-Based Models

Autor: Philippe Gorce, Vincent Hernandez, Nasser Rezzoug
Přispěvatelé: Université de Toulon (UTLN), Augmenting human comfort in the factory using cobots (AUCTUS), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Polytechnique de Bordeaux (Bordeaux INP), Tokyo University of Agriculture and Technology (TUAT), This work was financially supported by a grant (6533-2013) from the Ministry of National Education (France).
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Biomechanics
Biomechanics, MDPI, 2021, 1, pp.102-117. ⟨10.3390/biomechanics1010008⟩
Volume 1
Issue 1
Pages 8-117
Biomechanics, 2021, 1, pp.102-117. ⟨10.3390/biomechanics1010008⟩
ISSN: 2673-7078
DOI: 10.3390/biomechanics1010008⟩
Popis: A force capacity evaluation for a given posture may provide better understanding of human motor abilities for applications in sport sciences, rehabilitation and ergonomics. From data on posture and maximum isometric joint torques, the upper-limb force feasible set of the hand was predicted by four models called force ellipsoid, scaled force ellipsoid, force polytope and scaled force polytope, which were compared with a measured force polytope. The volume, shape and force prediction errors were assessed. The scaled ellipsoid underestimated the maximal mean force, and the scaled polytope overestimated it. The scaled force ellipsoid underestimated the volume of the measured force distribution, whereas that of the scaled polytope was not significantly different from the measured distribution but exhibited larger variability. All the models characterized well the elongated shape of the measured force distribution. The angles between the main axes of the modelled ellipsoids and polytopes and that of the measured polytope were compared. The values ranged from 7.3° to 14.3°. Over the entire surface of the force ellipsoid, 39.7% of the points had prediction errors less than 50 N
33.6% had errors between 50 and 100 N
and 26.8% had errors greater than 100N. For the force polytope, the percentages were 56.2%, 28.3% and 15.4%, respectively.
Databáze: OpenAIRE