Lower limb stiffness estimation during running: the effect of using kinematic constraints in muscle force optimization algorithms

The focus of this paper is on the effect of muscle force optimization algorithms on the human lower limb stiffness estimation. By using a forward dynamic neuromusculoskeletal model coupled with a muscle short-range stiffness model we computed the human joint stiffness of the lower limb during running. The joint stiffness values are calculated using two different muscle force optimization procedures, namely: Toque-based and Torque/Kinematic-based algorithm. A comparison between the processed EMG signal and the corresponding estimated muscle forces with the two optimization algorithms is provided. We found that the two stiffness estimates are strongly influenced by the adopted algorithm. We observed different magnitude and timing of both the estimated muscle forces and joint stiffness time profile with respect to each gait phase, as function of the optimization algorithm used.