Fig. 3

Summary of six optimization problems investigated in this study. Two optimizations used SynX to predict unmeasured muscle excitations (termed \(S{\text{yn}}X_{Unmeasured} + Params\) and \(S{\text{yn}}X_{{_{Unmeasured} }}^{Params}\)), three optimizations used static optimization (SO) to predict unmeasured muscle activations (termed \(SO_{{_{All} }}^{Generic}\), \(SO_{{_{All} }}^{Params}\) and \(SO_{{_{Unmeasured} }}^{Params}\)), and one “gold standard” optimization used the complete set of EMG signals with no muscle excitations predicted by SynX or SO (termed \(Params\)). The calibration cases were named based on the prediction method for unmeasured muscle excitations or activations as well as the categories of design variables included in the optimization problem formulation. The subscripts indicate which set of muscle excitations or activations were predicted computationally, while the superscripts indicate which set of model parameters were employed for calculating muscle activations and forces. In each column of the optimizations, the arrows indicate whether each group of muscle excitations or activations were predicted or obtained experimentally as well as which values were used if model parameters were not calibrated through optimization. The term “Scaled Generic” denotes scaled generic model parameter values, while “From Params” refers to the model parameter values derived from the “gold standard” (Params) optimization