Personalized body segment inertia parameters using 3D body scanner images
Résumé
Personalized values of Body Segment Inertia Parameters (BSIP) are necessary to perform dynamic analysis of human movement (e.g. trajectory of the whole body centre of mass trajectory for stability analysis, joint torques / muscular forces estimations, etc.). BSIPs are usually estimated using regressions derived from anthropometric tables (AT) [1]. However, these tables are usually not adapted to atypical populations (children, elderly, obese persons, individuals with prostheses, etc.) that are classically of interest. An alternative consists in estimating BSIPs from segments' volumes assuming a uniform density. This alternative is of growing interest as: 1) it would be suitable even for populations with atypical body mass repartition; 2) 3D body shapes acquisition has recently became easier and cheaper thanks to the developments of low-cost 3D scanners [2]. However, there are still some issues to makes this measurement (3D point cloud of the external shape) usable in the context of movement analysis with minimal intervention. The main issue is the segmentation of the whole body external shape into body segments with relevant local coordinate systems (LCS) and anatomical landmarks (AL) [3].
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