Joint torque analysis of push recovery motions during human walking

Most of their lifetime humans can recover from disturbances during walking motions very well. Our assumption is that to recover from disturbances during walking requires higher internal torques in the joints than motions without disturbances. To measure the internal joint torques in experiments is complicated and expensive. In this work we propose an optimality based simulation environment that allows to determine the internal torques in the joints of a human during disturbed walking motions. The human is represented by a two dimensional (2D) rigid multi-body model consisting of 14 segments controlled by torques in 13 rotational joints resulting in 16 degrees of freedom (DoF). The disturbance is modeled as external force acting on the model. A least-squares optimal control problem that minimizes the distance between the joint angles of the model and joint angles gained from motion capture experiments, while satisfying the dynamics and constraints of the human model, is set up. The analysis of perturbed and unperturbed walking motions shows that the torques in the joints vary according to the strength and duration of the disturbance. The calculation of the internal joint torques is important for the development of new control strategies or set up of humanoid robots and prostheses. It can also be used in the context of sport sciences to improve training or therapies.