| The traditional view of motor control predicates that the central nervous system dictates the motions of the body through muscle activation. An alternative view suggests that movement may be governed by body dynamics alone without need for neural control. Both philosophies have merits, but neither represents a complete solution for robust and efficient behavior. We proposed an integrated view of control and dynamics and investigated how the natural dynamics of the limbs influence control strategies used to pattern and stabilize walking. We explored how features of human walking, traditionally absent in passive walking models, are gained by adding compliance. This compliant behavior essentially models work performed by muscle and tendon and predicts energetic costs measured in human walking. We also countered the notion that walking and running can best be described by stiff and compliant leg behavior, respectively. We showed that the amount and proportion of mechanical energy in the legs distinguishes between gaits much more so than leg compliance or other properties. However, some control is needed to provide spring-like actuation and could be afforded by reflex loops and neural oscillators located in the spinal cord. We used a compliant walking model to study how the feedforward and feedback nature of central pattern generators (CPGs) can be optimally combined to produce steady walking motions. Our findings suggest that CPGs serve a primary role to filter sensory information rather than to simply generate motor commands. Finally, three-dimensional passive walkers indicate that the fore-aft component of walking may be self stable, whereas lateral motion remains unstable and requires control, as through active foot placement. We tested whether healthy humans exhibit such direction-dependent control by applying low-frequency perturbations to the visual field and measuring foot placement during treadmill walking. We found step variability to be nearly ten times more sensitive to lateral perturbations than fore-aft, suggesting that the central nervous system gains fore-aft stability through uncontrolled behavior. Our results may have implications for the development of novel prosthetics, more energy efficient robots, and the rehabilitation of a broad set of neuromuscular and physical disorders that cause locomotor impairment. |
