This study investigated the biomechanical loads and kinematics of workers during multiple-task manual material handling (MMH) jobs, and developed prediction models for the moments acting on a worker's body and their peak joint angles. An experiment was conducted in which 20 subjects performed a total of 3780 repetitions of a box-conveying task. This task included continuous sequential removing, carrying and depositing of boxes weighing 2-12 kg. The subjects' motion was captured using motion-capture technology. The origin/destination height was the most influencing predictor of the spinal and shoulder moments and the peak trunk, shoulder and knee angles. The relationship between the origin/destination heights and the above parameters was nonlinear. The mass of the box, and the subject's height and mass, also influenced the spinal and shoulder moments. A tradeoff between the moments acting on the L5/S1 vertebrae and on the shoulder joint was found. Compared to the models developed in similar studies that focused on manual material handling (albeit under different conditions), the high-order prediction equation for peak spinal moment formulated in the present study was found to explain between 10% and 48% more variability in the moments. This suggests that using a high-order equation in future studies might improve the prediction.

中文翻译：

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在多任务手动物料处理过程中，工人的生物力学负荷和运动学。

这项研究调查了多任务手动物料搬运（MMH）作业期间工人的生物力学负荷和运动学，并开发了作用于工人身体的时刻及其最大关节角度的预测模型。进行了一项实验，其中20名受试者共完成了3780次盒装运输任务的重复。这项任务包括连续顺序取出，搬运和存放2至12公斤重的箱子。使用运动捕捉技术捕获对象的运动。起点/终点高度是影响脊柱和肩部力矩以及躯干，肩部和膝关节顶角的最大影响因素。起点/终点高度与上述参数之间的关系是非线性的。盒子的重量，以及被摄对象的身高和体重，也影响了脊柱和肩部的力矩。发现在作用于L5 / S1椎骨和肩关节的力矩之间需要权衡。与专注于人工材料处理（尽管在不同条件下）的类似研究中开发的模型相比，发现本研究中制定的峰值脊柱弯矩的高阶预测方程式可解释10％至48％的差异。片刻。这表明在未来的研究中使用高阶方程可能会改善预测。发现本研究中制定的峰值脊柱弯矩的高阶预测方程式可以解释这些弯矩之间的差异在10％至48％之间。这表明在未来的研究中使用高阶方程可能会改善预测。发现本研究中制定的峰值脊柱弯矩的高阶预测方程式可以解释这些弯矩之间的差异在10％至48％之间。这表明在未来的研究中使用高阶方程可能会改善预测。