The three-compartment controller with enhanced recovery (3CC-r) model of muscle fatigue has previously been validated separately for both sustained (SIC) and intermittent isometric contractions (IIC) using different objective functions, but its performance has not yet been tested against both contraction types simultaneously using a common objective function. Additionally, prior validation has been performed using common parameters at the joint level, whereas applications to many real-world tasks will require the model to be applied to agonistic and synergistic muscle groups. Lastly, parameters for the model have previously been derived for a mixed-sex cohort not considering the differece in fatigabilities between the sexes. In this work we validate the 3CC-r model using a comprehensive isometric contraction database drawn from 172 publications segregated by functional muscle group (FMG) and sex. We find that prediction errors are reduced by 19% on average when segregating the dataset by FMG alone, and by 34% when segregating by both sex and FMG. However, minimum prediction errors are found to be higher when validated against both SIC and IIC data together using torque decline as the outcome variable than when validated sequentially against hypothesized SIC intensity-endurance time curves with endurance time as the outcome variable and against raw IIC data with torque decline as the outcome variable.

具有增强恢复 (3CC-r) 肌肉疲劳模型的三室控制器先前已使用不同的目标函数分别针对持续 (SIC) 和间歇性等长收缩 (IIC) 进行验证，但其性能尚未针对两者进行测试使用共同的目标函数同时收缩类型。此外，已经使用关节级别的通用参数进行了事先验证，而在许多实际任务中的应用将需要将模型应用于对抗性和协同性肌肉群。最后，该模型的参数先前是针对混合性别队列推导出来的，不考虑性别之间的疲劳差异。在这项工作中，我们使用综合等长收缩数据库验证 3CC-r 模型，该数据库来自 172 份按功能性肌肉群 (FMG) 和性别分类的出版物。我们发现，仅通过 FMG 分离数据集时，预测误差平均减少了 19%，而通过性别和 FMG 分离时，预测误差平均减少了 34%。然而，当使用扭矩下降作为结果变量同时针对 SIC 和 IIC 数据进行验证时，发现最小预测误差高于在针对假设的 SIC 强度-耐力时间曲线（以耐力时间作为结果变量）和原始 IIC 数据进行顺序验证时扭矩下降作为结果变量。当按性别和 FMG 进行隔离时，增加了 34%。然而，当使用扭矩下降作为结果变量同时针对 SIC 和 IIC 数据进行验证时，发现最小预测误差高于在针对假设的 SIC 强度-耐力时间曲线（以耐力时间作为结果变量）和原始 IIC 数据进行顺序验证时扭矩下降作为结果变量。当按性别和 FMG 进行隔离时，增加了 34%。然而，当使用扭矩下降作为结果变量同时针对 SIC 和 IIC 数据进行验证时，发现最小预测误差高于在针对假设的 SIC 强度-耐力时间曲线（以耐力时间作为结果变量）和原始 IIC 数据进行顺序验证时扭矩下降作为结果变量。