EMG-Driven Optimal Estimation of Subject-SPECIFIC Hill Model Muscle-Tendon Parameters of the Knee Joint Actuators
EMG-Driven Optimal Estimation of Subject-SPECIFIC Hill Model Muscle-Tendon Parameters of the Knee Joint Actuators
复制标题
DOI：
10.1109/tbme.2016.2630009
复制
发表时间：
2017-09-01
影响因子：
4.6
通讯作者：
De Groote, Friedl
中科院分区：
文献类型：
--
作者：
Falisse, Antoine;Van Rossom, Sam;De Groote, Friedl
目的：本文的目的是通过优化实验和基于模型的膝关节力矩之间的拟合，提出一种最优控制问题公式，以估计受试者特定的Hill模型膝关节执行器的肌肉-肌腱（MT-）参数。此外，本文旨在确定哪组功能运动包含必要的信息来识别mt参数。方法：利用肌电驱动的肌肉骨骼模型，通过直接配置的方式，解决了mt参数估计背后的最优控制和参数估计问题。包含足够信息来识别mt参数的运动集是通过评估基于受试者特定mt参数与实验力矩模拟的膝关节力矩来确定的。结果：在大约30 CPU min内解决了mt参数估计问题。在62组被调查的运动中，只有7组可以确定mt参数，这强调了实验方案的重要性。使用对象特定的mt参数而不是更常见的线性缩放mt参数，在决定系数方面（从0.57 +/- 0.20到0.74 +/- 0.14），将逆动力学力矩与模拟力矩之间的拟合提高了约30%，在均方根误差方面提高了约26%（从15.98 +/- 6.85到11.85 +/- 4.12 N）。米)。特别是，受试者特定的膝关节屈肌mt参数与线性缩放的mt参数非常不同。结论：我们引入了一个计算效率高的最优控制问题公式，并为设计实验方案提供了指导方针，以估计受试者特定的mt参数，提高运动模拟的准确性。意义：提出的公式为特定受试者的肌肉骨骼建模开辟了新的视角，这可能有助于模拟和理解病理运动。
Objective: the purpose of this paper is to propose an optimal control problem formulation to estimate subject-specific Hill model muscle-tendon (MT-) parameters of the knee joint actuators by optimizing the fit between experimental and model-based knee moments. Additionally, this paper aims at determining which sets of functional motions contain the necessary information to identify the MT-parameters. Methods: the optimal control and parameter estimation problem underlying the MT-parameter estimation is solved for subject-specific MT-parameters via direct collocation using an electromyography-driven musculoskeletal model. The sets of motions containing sufficient information to identify the MT-parameters are determined by evaluating knee moments simulated based on subject-specific MT-parameters against experimental moments. Results: the MT-parameter estimation problem was solved in about 30 CPU minutes. MT-parameters could be identified from only seven of the 62 investigated sets of motions, underlining the importance of the experimental protocol. Using subject-specific MT-parameters instead of more common linearly scaled MT-parameters improved the fit between inverse dynamics moments and simulated moments by about 30% in terms of the coefficient of determination (from 0.57 +/- 0.20 to 0.74 +/- 0.14) and by about 26% in terms of the root mean square error (from 15.98 +/- 6.85 to 11.85 +/- 4.12 N . m). In particular, subject-specific MT-parameters of the knee flexors were very different from linearly scaled MT-parameters. Conclusion: we introduced a computationally efficient optimal control problem formulation and provided guidelines for designing an experimental protocol to estimate subject-specific MT-parameters improving the accuracy of motion simulations. Significance: the proposed formulation opens new perspectives for subject-specific musculoskeletal modeling, which might be beneficial for simulating and understanding pathological motions.