Application of Newton/GMRES method to nonlinear model predictive control of functional electrical stimulation

Abstract

Recent studies have shown that functional electrical stimulation (FES) therapy can improve the motor recovery and range of the motion of stroke patients. The state-of-the-art functional electrical stimulators are open-loop control systems, i.e., the controller is unaware of the patient's posture and progress during the therapy. In this research, we have developed a closed-loop Newton/GMRES nonlinear model predictive controller that measures the patient posture and controls the muscle stimulation to reach a desired posture.