Relaxed individual control of skeletal muscle forces via physical human–robot interaction

This study develops a relaxed formulation of a method for controlling individual muscle forces using exoskeleton robots. Past studies have developed a muscle-force control method with very strict limitations on the conditions. These conditions will be removed, and the problem will be reformulated as a constrained optimization of several parameters. The optimization algorithm recognizes when a solution to the muscle control problem cannot be exactly realized, and finds the solution that minimizes the mean errors of the individual muscles between expected and desired muscle activation. This is demonstrated in a computer simulation of human arm dynamics and compared against the prior method to demonstrate its wider applicability. In addition, the control method is extended to resolve issues associated with a nonideal exoskeleton with incomplete torque application to the joints. A quasi-optimized motor-task that minimizes the errors in target muscles and nontarget muscles can be obtained. This paper presents theoretical analysis, simulation, and experimental results on the performance of the relaxed individual muscle control.