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.

中文翻译：

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在使用惯性运动捕捉的人工材料处理过程中估算脊柱负荷。

传统上，肌肉骨骼模型依赖于基于标记运动捕捉和地面力板的节段运动学和地面反作用力和力矩（GRF＆M）的测量，这些运动通常限于实验室环境。惯性运动捕获（IMC）的最新进展以及预测GRF＆M的方法已使现场采集这些输入数据成为可能。因此，这项研究评估了一种新颖的方法的并行有效性，该方法基于仅使用IMC数据和预测的GRF＆Ms驱动的肌肉骨骼模型来估计手动材料处理过程中腰椎的动态负荷。行李箱运动学，GRF＆M，将13名执行各种举升和转移任务的受试者的L4-L5关节反作用力（JRF）和直立脊柱肌力与同时记录的皮肤标记轨迹和测力板数据驱动的模型进行了比较。在对称和不对称举升过程中，L4-L5轴向压缩，竖脊肌和垂直地面反作用力的相关性中等至极好，但模型之间也存在差异，特别是躯干运动学和L4- L5剪切力。基于这些结果，提出的方法可用于在现场人工处理物料的动态条件下，估计相对的L4-L5轴向压缩力。