Accuracy and kinematics consistency of marker-based scaling approaches on a lower limb model: a comparative study with imagery data

P. Puchaud, C. Sauret, A. Muller, N. Bideau, G. Dumont, H. Pillet and C. Pontonnier

Computer Methods in Biomechanics and Biomedical Engineering, 2020, vol. 23, issue 3, 114-125

Abstract: Medical images are not typically included in protocol of motion laboratories. Thus, accurate scaling of musculoskeletal models from optoelectronic data are important for any biomechanical analysis. The aim of the current study was to identify a scaling method based on optoelectronic data, inspired from literature, which could offer the best trade-off between accurate geometrical parameters (segment lengths, orientation of joint axes, marker coordinates) and consistent inverse kinematics outputs (kinematic error, joint angles). The methods were applied on 26 subjects and assessed with medical imagery building EOS-based models, considered as a reference. The main contribution of this paper is to show that the marker-based scaling followed by an optimisation of orientation joint axes and markers local coordinates, gives the most consistent scaling and joint angles with EOS-based models. Thus, when a non-invasive mean with an optoelectronic system is considered, a marker-based scaling is preliminary needed to get accurate segment lengths and to optimise joint axes and marker local coordinates to reduce kinematic errors.AbbrevationsAJCAnkle joint centreCKEcumulative kinematic errorDoFdegree of freedomEBEOS-basedHBheight-basedHJChip joint centreKJCknee joint centreMBmarker-basedMSMmusculoskeletal modelsSPMstatistical parametric mappingSTAsoft tissue artifactEBa.m∗EOS-based with optimised joint axes, and all model markers coordinatesMBa.m∗marker-based with optimised joint axes, and all model markers coordinatesMBl.a.mmarker-based with optimised segment lengths, joint axes, and selected model markers coordinatesASISanterior superior illiac spinePSISposterior superior illiac spine

Date: 2020
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DOI: 10.1080/10255842.2019.1705798

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