使用骨骼运动优化结果作为输入数据的OpenSim肌肉力预测

Rahid Zaman, Y. Xiang, Ritwik Rakshit, Jie Yang
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引用次数: 4

摘要

本文描述了一种集成方法,通过集成预测骨骼模型和OpenSim来预测举重过程中人体腿部和脊柱肌肉的力量。首先采用逆动力学优化方法对二维骨架提升运动进行了预测。然后,将关节角度轮廓、地面反作用力和压力中心等预测输出整合到OpenSim生物力学软件中,分析肌肉力量。因此,该综合方法在肌肉骨骼水平上具有预测能力。通过这种方法,我们可以预测和分析举重运动中肌肉的受力,而这是很难用三维肌肉骨骼模型直接模拟的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Muscle Force Prediction in OpenSim Using Skeleton Motion Optimization Results As Input Data
This paper describes an integrated approach to predict human leg and spine muscle forces during lifting by integration of a predictive skeletal model with OpenSim. The two-dimensional (2D) skeletal lifting motion is first predicted by using an inverse dynamics optimization method. Then, the prediction outputs, including joint angle profiles, ground reaction forces, and center of pressure, are incorporated in OpenSim biomechanics software to analyze muscle forces for lifting. Therefore, the integrated approach has predictive capability on musculoskeletal level. By using this method, we can predict and analyze muscles forces for heavy weight lifting motion which is difficult to simulate directly using a 3D musculoskeletal model.
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