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使用惯性运动捕捉估计手动搬运材料过程中的脊柱负荷。

Estimation of Spinal Loading During Manual Materials Handling Using Inertial Motion Capture.

机构信息

Sport Sciences, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.

Department of Materials and Production, Aalborg University, Aalborg, Denmark.

出版信息

Ann Biomed Eng. 2020 Feb;48(2):805-821. doi: 10.1007/s10439-019-02409-8. Epub 2019 Nov 20.

Abstract

Musculoskeletal models have traditionally relied on measurements of segment kinematics and ground reaction forces and moments (GRF&Ms) from marked-based motion capture and floor-mounted force plates, which are typically limited to laboratory settings. Recent advances in inertial motion capture (IMC) as well as methods for predicting GRF&Ms have enabled the acquisition of these input data in the field. Therefore, this study evaluated the concurrent validity of a novel methodology for estimating the dynamic loading of the lumbar spine during manual materials handling based on a musculoskeletal model driven exclusively using IMC data and predicted GRF&Ms. Trunk kinematics, GRF&Ms, L4-L5 joint reaction forces (JRFs) and erector spinae muscle forces from 13 subjects performing various lifting and transferring tasks were compared to a model driven by simultaneously recorded skin-marker trajectories and force plate data. Moderate to excellent correlations and relatively low magnitude differences were found for the L4-L5 axial compression, erector spinae muscle and vertical ground reaction forces during symmetrical and asymmetrical lifting, but discrepancies were also identified between the models, particularly for the trunk kinematics and L4-L5 shear forces. Based on these results, the presented methodology can be applied for estimating the relative L4-L5 axial compression forces under dynamic conditions during manual materials handling in the field.

摘要

肌肉骨骼模型传统上依赖于基于标记的运动捕捉和地面安装力板的节段运动学和地面反作用力矩 (GRF&Ms) 的测量,这些方法通常仅限于实验室环境。最近惯性运动捕捉 (IMC) 的进步以及预测 GRF&Ms 的方法使得这些输入数据可以在现场获取。因此,本研究评估了一种基于仅使用 IMC 数据和预测的 GRF&Ms 驱动的肌肉骨骼模型来估计手动搬运过程中腰椎动态负荷的新方法的同时有效性。比较了 13 名受试者在执行各种提升和转移任务时的躯干运动学、GRF&Ms、L4-L5 关节反作用力 (JRF) 和竖脊肌肌肉力,与同时记录的皮肤标记轨迹和力板数据驱动的模型。在对称和不对称提升过程中,L4-L5 轴向压缩、竖脊肌和垂直地面反作用力的相关性适中到极好,并且差异相对较小,但模型之间也存在差异,特别是对于躯干运动学和 L4-L5 剪切力。基于这些结果,所提出的方法可用于在现场手动搬运过程中估计动态条件下相对 L4-L5 轴向压缩力。

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