Modeling and prediction of body segment inertial properties of sheep from tomographic imaging

基于断层成像技术的绵羊体节惯性特性建模与预测

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Abstract

Sheep are frequently used animal models of musculoskeletal diseases and orthopedic procedures due to their docility, size and body weight, and similar joint biomechanics to humans. Estimation of body segment inertial properties (BSIPs) is a crucial step in development of biomechanical models, but few resources exist for BSIPs in sheep. The goal of this study was to develop predictive models to estimate the mass, center of mass, and inertia tensor of the hindlimbs of sheep from easily obtainable morphometric data. In addition, this study presents a more comprehensive and repeatable method for defining each hindlimb body segment when directly calculating BSIPs from tomographic imaging. Briefly, CT scans from 16 sheep of varying age, weight, sex, and phenotype were used to calculate BSIPs for the pelvis, thigh, crus, metatarsus, and pastern segments. Those measurements were then used to develop predictive models to estimate the BSIPs for those segments. The predictive models developed showed similar prediction errors to models developed in human populations.

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