Swing leg control in human running

Abstract

Humans can run within a wide range of speeds without thinking about stabilizing strategies. The leg properties seem to be adjusted automatically without need for sensory feedback. In this work, the dynamics of human running are represented by the planar spring mass model. Within this framework, for higher speeds, running patterns can be stable without control strategies. Here, potential strategies that provide stability over a broader range of running patterns are considered and these theoretical predictions are compared to human running data. Periodic running solutions are identified and analyzed with respect to their stability. The control strategies are assumed as linear adaptations of the leg parameters—leg angle, leg stiffness and leg length—during the swing phase. To evaluate the applied control strategies regarding their influence on landing behavior, two parameters are introduced: the velocity of the foot relative to the ground (ground speed matching) and the foot's angle of approach. The results show that periodic running solutions can be stabilized and that control strategies, which guarantee running stability, are redundant. For any swing leg kinematics (adaptation of the leg angle and the leg length), running stability can be achieved by adapting the leg stiffness in anticipation of the ground contact.