School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, K1N 6N5, Canada.
Department of Mechanical Engineering, University of Ottawa, Ottawa, ON, K1N 6N5, Canada.
Ann Biomed Eng. 2024 Feb;52(2):259-269. doi: 10.1007/s10439-023-03368-x. Epub 2023 Sep 23.
A fully articulated thoracolumbar spine model had been previously developed in OpenSim and had been extensively validated against experimental data during various static tasks. In the present study, we enhanced this detailed musculoskeletal model by adding the role of passive structures and adding kinematic constraints to make it suitable for dynamic tasks. We validated the spinal forces estimated by this enhanced model during nine dynamic lifting/lowering tasks. Moreover, we recently developed and evaluated five approaches in OpenSim to model the external loads applied to the hands during lifting/lowering tasks, and in the present study, we assessed which approach results in more accurate spinal forces. Regardless of the external load modeling approach, the maximum forces predicted by our enhanced spine model across all tasks, as well as the pattern of estimated spinal forces within each task, showed strong correlations (r-values and cross-correlation coefficients > 0.9) with experimental data. Given the biofidelity of our enhanced model, its accessibility via the open-source OpenSim software, and the extent to which this model has been validated, we recommend it for applications requiring estimation of spinal forces during lifting/lowering tasks using multibody-based models and inverse dynamic analyses.
一个全关节胸腰椎模型先前已在 OpenSim 中开发，并在各种静态任务中针对实验数据进行了广泛验证。在本研究中，我们通过添加被动结构的作用并添加运动学约束来增强这个详细的肌肉骨骼模型，使其适合动态任务。我们验证了该增强模型在九项动态举升/下降任务中估计的脊柱力。此外，我们最近在 OpenSim 中开发并评估了五种方法来模拟举升/下降任务中施加到手的外部负载，在本研究中，我们评估了哪种方法导致更准确的脊柱力。无论采用哪种外部负载建模方法，我们增强的脊柱模型在所有任务中预测的最大力，以及在每个任务中估计的脊柱力的模式，都与实验数据显示出很强的相关性（r 值和互相关系数>0.9）。鉴于我们增强模型的生物逼真度、通过开源 OpenSim 软件的可访问性以及该模型的验证程度，我们建议在需要使用多体模型和逆动力学分析来估计举升/下降任务中的脊柱力的应用中使用它。
