The overall aim of this project is to develop a technique for specifying the motor coordination strategies that the central nervous system (CNS) ought to employ in order to execute a specific, but complex motor task. The technique under development is based on optimal control theory which is a highly developed framework for analysis of complex dynamical systems. Once developed, the technique may well lead to improved methods for rehabilitative training and physical therapy, for reconstructive orthopaedic surgery, and for the training of athletes. Optimal control theory requires a mathematical formulation of the task to be optimized. The major problem associated with the few previous attempts employing such theory is that the performance criterion cannot be specified with certainty. This project circumvents this problem by studying maximum jumps and pedaling at high effort. With this problem resolved, this project will focus on the development of a mathematical, computer-implemented representation of the musculoskeletal system of the human leg. The emphasis will be on the development of computer descriptions of muscle and tendon based on their architecture and the properties of sarcomeres. This development depends on the comparison, to be made in this project, of body trajectory, ground reaction forces and joint torques that humans ought to produce with the trajectory, forces and torques actually generated by human subjects who pedal or jump. The optimal control model will then be used to determine, among other things, how physique, coordination and elastic storage of energy in muscle and tendon affect overall performance and the details of body movement. The coordination strategy to be found using the above technique will be the one that is optimal, given that there is no restriction on the motor output pattern that the CNS can generate. This assumption may be invalid for unfamiliar tasks. Comparison of the coordination used by subjects who perform novel pedaling tasks with the coordination that ought to be used in the absence of CNS constraints will be analyzed to find the operational characteristics of the constraints.