Dynamic stability and phase resetting during biped gait.

Dynamic stability during periodic biped gait in humans and in a humanoid robot is considered. Here gait systems of human neuromusculoskeletal system and a humanoid are simply modeled while keeping their mechanical properties plausible. We prescribe periodic gait trajectories in terms of joint angles of the models as a function of time. The equations of motion of the models are then constrained by one of the prescribed gait trajectories to obtain types of periodically forced nonlinear dynamical systems. Simulated gait of the models may or may not fall down during gait, since the constraints are made only for joint angles of limbs but not for the motion of the body trunk. The equations of motion can exhibit a limit cycle solution (or an oscillatory solution that can be considered as a limit cycle practically) for each selected gait trajectory, if an initial condition is set appropriately. We analyze the stability of the limit cycle in terms of Poincaré maps and the basin of attraction of the limit cycle in order to examine how the stability depends on the prescribed trajectory. Moreover, the phase resetting of gait rhythm in response to external force perturbation is modeled. Since we always prescribe a gait trajectory in this study, reacting gait trajectories during the phase resetting are also prescribed. We show that an optimally prescribed reacting gait trajectory with an appropriate amount of the phase resetting can increase the gait stability. Neural mechanisms for generation and modulation of the gait trajectories are discussed.