Koo Terry K K, Mak Arthur F T, Hung L K
Jockey Club Rehabilitation Engineering Centre, The Hong Kong Polytechnic University, Hung Hom, Kowloon, China.
Clin Biomech (Bristol). 2002 Jun;17(5):390-9. doi: 10.1016/s0268-0033(02)00031-1.
This study aimed at estimating the musculotendon parameters of the prime elbow flexors in vivo for both normal and hemiparetic subjects.
A neuromusculoskeletal model of the elbow joint was developed incorporating detailed musculotendon modeling and geometrical modeling.
Neuromusculoskeletal modeling is a valuable tool in orthopedic biomechanics and motor control research. However, its reliability depends on reasonable estimation of the musculotendon parameters. Parameter estimation is one of the most challenging aspects of neuromusculoskeletal modeling.
Five normal and five hemiparetic subjects performed maximum isometric voluntary flexion at nine elbow positions (0 degrees -120 degrees of flexion with an increment of 15 degrees ). Maximum flexion torques were measured at each position. Computational optimization was used to search for the musculotendon parameters of four prime elbow flexors by minimizing the root mean square difference between the predicted and the experimentally measured torque-angle curves.
The normal group seemed to have larger maximum muscle stress values as compared to the hemiparetic group. Although the functional ranges of each selected muscle were different, they were all located at the ascending limb of the force-length relationship. The muscle optimal lengths and tendon slack lengths found in this study were comparable to other cadaver studies reported in the literature.
Subject-specific musculotendon parameters could be properly estimated in vivo.
Estimation of subject-specific musculotendon parameters for both normal and hemiparetic subjects would help clinicians better understand some of the effects of this pathological condition on the musculoskeletal system.
本研究旨在估计正常和偏瘫受试者体内主要肘关节屈肌的肌腱参数。
开发了一个肘关节的神经肌肉骨骼模型,该模型纳入了详细的肌腱建模和几何建模。
神经肌肉骨骼建模是骨科生物力学和运动控制研究中的一种有价值的工具。然而,其可靠性取决于肌腱参数的合理估计。参数估计是神经肌肉骨骼建模中最具挑战性的方面之一。
五名正常受试者和五名偏瘫受试者在九个肘关节位置(0度至120度屈曲,增量为15度)进行最大等长自愿屈曲。在每个位置测量最大屈曲扭矩。通过最小化预测扭矩-角度曲线与实验测量扭矩-角度曲线之间的均方根差,使用计算优化来搜索四个主要肘关节屈肌的肌腱参数。
与偏瘫组相比,正常组似乎具有更大的最大肌肉应力值。虽然每个选定肌肉的功能范围不同,但它们都位于力-长度关系的上升支。本研究中发现的肌肉最佳长度和肌腱松弛长度与文献中报道的其他尸体研究结果相当。
可以在体内正确估计个体特异性的肌腱参数。
估计正常和偏瘫受试者的个体特异性肌腱参数将有助于临床医生更好地理解这种病理状况对肌肉骨骼系统的一些影响。