The benefits of optimization-based modeling for parameter estimation of Hill-type muscle models are demonstrated. Therefore, we examined the model and data of Günther et al. (2007), who analyzed isometric, concentric, and quick-release contractions of a piglet calf muscle. We found that the isometric experiments are suitable for derivative-based parameter estimation while the others did not provide any additional value. During the estimation process, certain parameters had to be fixed. We give possible reasons and provide impulses for modelers. Subsequently, unnecessarily complex or deprecated model parts were exchanged and the new model was fitted to the data. In order to be able to provide a reliable estimation of the whole parameter set, we propose two isometric and two quick-release experiments, which are real-life feasible and together allow an identification of all parameters based on a local sensitivity analysis. These experiments can be used as qualitative guidelines for practitioners to reduce the experimental effort when estimating parameters for macroscopic muscle models.

展示了基于优化的建模对Hill型肌肉模型的参数估计的好处。因此，我们检查了Günther等人的模型和数据。（2007年），他分析了仔猪小腿肌肉的等距，同心和快速释放收缩。我们发现等轴实验适合于基于导数的参数估计，而其他实验则没有提供任何附加值。在估算过程中，必须固定某些参数。我们给出可能的原因并为建模者提供动力。随后，交换了不必要的复杂或过时的模型零件，并将新模型拟合到数据中。为了能够对整个参数集提供可靠的估算，我们提出了两个等距和两个快速释放实验，它们是现实可行的，并且可以一起基于局部灵敏度分析来识别所有参数。这些实验可以用作从业人员的定性指南，以减少估算宏观肌肉模型参数时的实验工作量。