Henry Aaron, Benner Carson M, Covan Bailee, Helin Annabelle, Gaddy Dana, Suva Larry, Robbins Andrew B
bioRxiv. 2025 May 6:2025.04.30.651518. doi: 10.1101/2025.04.30.651518.
Estimation of body segment inertial properties (BSIPs) is a crucial step in development of inverse dynamics models. 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 using easily obtainable morphometric data. In addition, this study presents a more comprehensive and repeatable method for defining each hindlimb body segment when calculating BSIPs from CT data. CT scans from 16 sheep of varying age, weight, sex, and phenotype were used to develop predictive models to estimate the BSIPs of the pelvis, thigh, crus, metatarsus, and pastern segments. The predictive models developed enable investigators to create inverse dynamics models of sheep hindlimbs. These models are particularly informative and expand the use of ovine models of human musculoskeletal disease.
估计身体节段惯性特性(BSIPs)是逆动力学模型开发中的关键步骤。本研究的目的是开发预测模型,利用易于获取的形态测量数据来估计绵羊后肢的质量、质心和惯性张量。此外,本研究提出了一种更全面、可重复的方法,用于在从CT数据计算BSIPs时定义每个后肢身体节段。使用来自16只年龄、体重、性别和表型各异的绵羊的CT扫描数据来开发预测模型,以估计骨盆、大腿、小腿、跖骨和掌骨节段的BSIPs。所开发的预测模型使研究人员能够创建绵羊后肢的逆动力学模型。这些模型特别具有信息价值,并扩展了人类肌肉骨骼疾病绵羊模型的应用。