Dynamic knee simulators aim to reproduce prescribed physiological loading and motions of the knee. The natural knee achieves stability through a complex interaction of the neuro-musculoskeletal system; thus, a knee simulator also requires a sophisticated control system to replicate human motion. Guess and Maletsky [1] developed a computational model to predict the required simulator inputs to produce the desired knee loading for dynamic activities on the Kansas Knee Simulator (KKS). The model built demonstrated conceptually that multi-body dynamics models could be used to simulate the KKS. However, as desired loading profiles became more complex, key limitations were discovered in the model; such as the model controller limited to a single axis under feedback control, no out-of-plane loading, not accounting for dynamic joint friction or damping of the actuators, and an inability of the model to flex pass 80° degrees of knee flexion. Thus, there was a need for a new computational model to overcome the limitations and to provide a more robust and complete comparison to the KKS. The new computational model will allow better utilization of the KKS capabilities for future cadaveric and prosthetic testing. This work outlines the sagittal-plane validation of the new computational model.

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