Title: Degrees of freedom coupling adapted to the upper limb of a digital human model

Authors: Pierre-Olivier Lemieux; Arnaud Barré; Nicola Hagemeister; Rachid Aissaoui

Addresses: Département de génie de la production automatisée, École de technologie supérieure (ÉTS), 1100 Notre-Dame Ouest, H3C 1K3, Montreal, Canada ' Centre de développement et de recherche en imagerie numérique (CDRIN), 608, avenue Saint-Rédempteur, G4W 0E1, Matane, Québec, Canada ' Centre de recherche du CHUM, 900 Rue Saint-Denis, Montréal, Québec, H2X 0A9, Canada ' Centre de recherche du CHUM, 900 Rue Saint-Denis, Montréal, Québec, H2X 0A9, Canada

Abstract: The upper limbs of digital human models have many degrees of freedom. Moreover, their range of motion tends to be overestimated. In some conditions, the resulting kinematic chain may predict unrealistic postures. Many kinematic correlations or 'couplings' have been measured at the upper limb (ex. shoulder rhythm, sinus cone limits). So far, a few of them were adapted to digital human models. These models often use a simplified 'claviscapular' segment, which simplifies the shoulder girdle, (i.e., clavicle and scapula) as a single segment. This paper presents the development of a set of upper limb degree of freedom couplings for digital human models, adapted from experimental kinematic data that comes from different published studies. It is shown how these couplings improve the upper limb model by reducing its overestimated ranges of motion and reachable workspace and by improving its kinematic behaviour. The use of experimental data from a single group of subjects is the next step towards a more homogeneous upper limb coupling model.

Keywords: digital human model; DHM; shoulder rhythm; range of motion; ROM; degree of freedom; DOF; sinus cone limits; claviscapular segment; scapulohumeral rhythm; posture; inverse kinematics; IK; reachable workspace.

DOI: 10.1504/IJHFMS.2017.087015

International Journal of Human Factors Modelling and Simulation, 2017 Vol.5 No.4, pp.314 - 337

Received: 26 Dec 2016
Accepted: 21 May 2017

Published online: 28 Sep 2017 *

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