Investigation of Feedback Control Systems for Functional Electrical Stimulation Using a Two-Dimensional Upper Limb Model

Abstract

Objective: Assistive functional electrical stimulation (FES) is the complete artificial replacementof motor function through coordinated electrical stimulation of muscles. Successful clinical instances of assistive FES have so far been limited in scope due to a number of longstanding challenges. Among these are the need for robust feedback control systems capable of compensating for biological noise and inconsistency associated with muscular actuators, as well as smoothing over natural instability associated with driving a complex mechanical assembly like the human body. Approach: A two-dimensional upper limb model was constructed to function as a relatively inexpensive testbed for possible assistive FES feedback control systems prior to their experimental use. This model was then used to test two feedback control systems: joint PID controllers acting through precisely prescribed muscular actuators similar to the CMC system of OpenSim/SIMM, and an artificial neural network trained to predict muscle activations from kinematic data. Main Results: The joint PID controller system of OpenSim/SIMM was confirmed to be an effective, but experimentally infeasible method of FES feedback control. The artificial neural network controller was found to be ineffective. Significance: An account of building a biomechanical link-segment model capable of inverse and forward dynamic simulation from the ground up is herein provided. Test results from this model using theoretical FES feedback control systems are presented and discussed.