The influence of system dynamics on the control and energetics of repetitive human movement

Repetitive human movement is not a feed-forward process, but one in which control, actuation, and dynamics are tightly linked. Humans tend to move in a way that minimizes the energetic cost of actuation while choosing a control strategy that maintains stability. Through experiments and computational modeling, we will show that the mechanical properties, or dynamics, of the body play a large role in determining energetic demand and the control strategy.; System dynamics are an important factor in the energetic cost of a simple, one degree of freedom oscillatory task. The frequency dependent relationship between muscle activity and force generation identified the natural frequency of the system, the same frequency at which energetic demand was minimized. A model of the mechanical parameters of the system was able to fit this relationship and predict the contributions of muscle and tendon to the total mechanical energy of the system, and the costs of generating the oscillations. At low frequencies the energetic demand was dominated by the cost of doing muscular work, while at higher speeds the main cost was due to generating large forces at a high rate.; Artificially altering the dynamics can improve the performance of some movements, including leg swing, a significant contributor to the cost of walking. Adding an external stiffness about the hip increased the natural frequency of leg swing, decreased muscle activity about the joint, and lowered energetic costs at higher swing rates. An uncontrolled, weakly powered model of walking predicted that changing the dynamics by adding passive stiffness about the joints could generate faster gaits.; Dynamics can also be changed to stabilize a system, removing the need for active control. When lateral sway in walking, a naturally unstable motion, was stabilized by adding external stiffness to the dynamic system, the control strategy changed as step width and step width variability decreased. Young subjects chose a control strategy that decreased energetic demand, while older subjects preferred a higher stability margin.; Using models and experiments, we demonstrated that the dynamics of a system influences the energetics and control of repetitive movement, and can potentially be altered to improve performance.