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SUBJECT-SPECIFIC AND FUNCTION-SPECIFIC APPLICABILITY OF A HAND-FOREARM MUSCULOSKELETAL MODEL

机译:臂力型肌肉骨骼模型的对象特定性和功能特定性适用性

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There is ambiguity on the quantitative validity of the predictions revealed by musculoskeletal models for muscle forces. This study investigated the consistency between the predictions of a musculoskeletal model of the upper limb and the experimental data for a number of different subjects and functional tasks. Six normal subjects performed isokinetic eccentric or isotonic concentric contraction tests of the wrist muscles in well controlled conditions, using a robotic apparatus, and the net joint torque and angular velocities, as well as the surface electromyograms (EMG) signals of the muscles, were recorded. The experiments were then simulated using a parametric musculoskeletal model of hand and forearm, scaled for each subject. Muscle activation was determined based on the optimization of a polynomial or min-max objective function. Comparison of the model predictions with the normalized EMGs revealed more consistent results for the polynomial objective function. In general, the model could reflect the change of the net joint torque on the activation level, but the effects associated with the velocity of movement were not sufficiently reflected. Stronger correlations between model predictions and normalized EMGs, were obtained for subjects with smaller body mass indices (BMIs), 0.738, and those who experienced higher muscular excitations, 0.908. The sensitivity analysis of the model also indicated a high sensitivity (9.5%) to the joint torque but a minimal sensitivity (0.3%) to the joint velocity. The sensitivity indices for the muscle's length and physiological cross-sectional area (PCSA) were 11.2 and 5.3%, respectively. It was concluded that our musculoskeletal model was highly sensitive to the anatomical data, as well as the muscles' excitation levels, but not to the contraction velocity.
机译:肌肉骨骼模型对肌肉力量的预测的定量有效性存在歧义。这项研究调查了上肢肌肉骨骼模型的预测与许多不同主题和功能任务的实验数据之间的一致性。六名正常受试者使用机器人设备在受控条件下对腕部肌肉进行了等速离心或等张同心收缩测试,并记录了净关节扭矩和角速度以及肌肉的表面肌电图(EMG)信号。然后使用手和前臂的参数肌肉骨骼模型对实验进行模拟,并针对每个对象进行缩放。基于多项式或最小-最大目标函数的优化来确定肌肉激活。将模型预测值与规范化的EMG进行比较,发现多项式目标函数的结果更加一致。通常,该模型可以反映净关节扭矩在激活水平上的变化,但是与运动速度相关的影响并未得到充分反映。对于体重指数(BMI)较小的受试者(0.738)和肌肉兴奋度较高的受试者(0.908),模型预测与标准化EMG之间的相关性更强。该模型的敏感性分析还表明,对关节扭矩的敏感性较高(9.5%),但对关节速度的敏感性最小(0.3%)。肌肉长度和生理截面积(PCSA)的敏感度指数分别为11.2%和5.3%。结论是,我们的肌肉骨骼模型对解剖数据以及肌肉的兴奋水平高度敏感,但对收缩速度不敏感。

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