Department of Electrical and Computer Engineering, University of Patras, Greece.
J Biomech. 2019 Mar 6;85:101-107. doi: 10.1016/j.jbiomech.2019.01.017. Epub 2019 Jan 22.
This work presents a framework for computing the limbs' stiffness using inverse methods that account for the musculoskeletal redundancy effects. The musculoskeletal task, joint and muscle stiffness are regulated by the central nervous system towards improving stability and interaction with the environment during movement. Many pathological conditions, such as Parkinson's disease, result in increased rigidity due to elevated muscle tone in antagonist muscle pairs, therefore the stiffness is an important quantity that can provide valuable information during the analysis phase. Musculoskeletal redundancy poses significant challenges in obtaining accurate stiffness results without introducing critical modeling assumptions. Currently, model-based estimation of stiffness relies on some objective criterion to deal with muscle redundancy, which, however, cannot be assumed to hold in every context. To alleviate this source of error, our approach explores the entire space of possible solutions that satisfy the action and the physiological muscle constraints. Using the notion of null space, the proposed framework rigorously accounts for the effect of muscle redundancy in the computation of the feasible stiffness characteristics. To confirm this, comprehensive case studies on hand movement and gait are provided, where the feasible endpoint and joint stiffness is evaluated. Notably, this process enables the estimation of stiffness distribution over the range of motion and aids in further investigation of factors affecting the capacity of the system to modulate its stiffness. Such knowledge can significantly improve modeling by providing a holistic overview of dynamic quantities related to the human musculoskeletal system, despite its inherent redundancy.
这项工作提出了一种使用逆方法计算肢体刚度的框架，该方法考虑了肌肉骨骼冗余效应。肌肉骨骼任务、关节和肌肉刚度由中枢神经系统调节，以提高运动过程中的稳定性和与环境的相互作用。许多病理状况，如帕金森病，由于拮抗肌对的肌肉张力升高而导致刚性增加，因此刚度是在分析阶段提供有价值信息的重要数量。肌肉骨骼冗余在不引入关键建模假设的情况下获得准确的刚度结果方面带来了重大挑战。目前，基于模型的刚度估计依赖于一些客观标准来处理肌肉冗余，但不能假设在每种情况下都适用。为了减轻这种误差源，我们的方法探索了满足动作和生理肌肉约束的所有可能解决方案的空间。使用零空间的概念，所提出的框架严格考虑了肌肉冗余在可行刚度特性计算中的影响。为了证实这一点，提供了对手部运动和步态的综合案例研究，评估了可行的端点和关节刚度。值得注意的是，这个过程可以估计运动范围内的刚度分布，并有助于进一步研究影响系统调节其刚度能力的因素。这种知识可以通过提供与人体肌肉骨骼系统相关的动态数量的整体概述，尽管存在固有冗余，从而显著改进建模。
