Human-Centric Design Research Lab, Department of Mechanical Engineering, Texas Tech University, Lubbock, TX 79409, USA.
School of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK 74078, USA.
J Biomech. 2022 Aug;141:111224. doi: 10.1016/j.jbiomech.2022.111224. Epub 2022 Jul 18.
The three-compartment-controller with enhanced recovery (3CC-r) model of fatigue has been validated, in multiple stages and by different methods, for sustained (SIC) and intermittent isometric contractions (IIC). It has also been validated using a common methodology for both contraction types simultaneously to derive sex-specific representative model parameters for each functional muscle group, at the expense of reducing the sample size used to estimate each parameter set. In this study, a sensitivity analysis of the model to both variations in experimental measurements and to variations in the parameter values is carried out to estimate the robustness of the parameter sets. Torque decline prediction error is found to increase only slowly with increasing randomness injected into experimental data, with <1 % increases in error for 8-29 % variation in experimental endurance times. The results demonstrate that the obtained parameters from our previous study are reliable and can be used for fatigue prediction in multiple scenarios without significant loss of accuracy. For all sexes and functional muscle groups examined, the fatigue process dominates recovery in the experimental conditions examined. Finer estimates of the model's recovery parameter will likely require changes to the experiment design in future studies.
已经通过多个阶段和不同的方法验证了具有增强恢复功能的三腔控制器(3CC-r)疲劳模型,适用于持续(SIC)和间歇等长收缩(IIC)。该模型还使用了一种通用方法来同时验证这两种收缩类型,以便为每个功能肌肉群得出具有代表性的性别特异性模型参数,这是以减少用于估计每个参数集的样本量为代价的。在这项研究中,对模型进行了灵敏度分析,以评估其对实验测量和参数值变化的稳健性。发现转矩下降预测误差仅随实验数据中注入的随机性缓慢增加,实验耐力时间变化 8-29%时,误差增加<1%。结果表明,我们之前研究中获得的参数是可靠的,可以在没有显著降低准确性的情况下,在多种情况下用于疲劳预测。对于所有性别和功能肌肉群,在检查的实验条件下,疲劳过程主导恢复。在未来的研究中,可能需要对实验设计进行更改,以更精细地估计模型的恢复参数。