Can Iterative Learning Control (ILC) mediated by Functional Electrical Stimulation (FES) be used in the re-education of upper limb function

Patients with post-stroke hemiplegia may have impaired upper limb function related to motor control, weakness and spasticity. Evidence has shown that robotic therapy or Functional Electrical Stimulation can improve impairment levels and possibly function. To date there has been limited research into possible benefits gained by combining the two techniques. This is also true of the application of Iterative Learning Control to problems that are not concerned with industrial processes. The aim of this project is to test the feasibility of re-educating upper limb movement post stroke, using ILC mediated by FES using a robot. In the initial phase of this project, models have been created using data from eight neurologically intact subjects. Muscle activity was recorded using surface electromyography in a cross sectional observation study during which participants undertook tracking tasks using nine different trajectories, with their forearm constrained in a two dimensional plane by a robot. Kinematic and kinetic data was then collected, used to produce a dynamic model for each subject and to derive iterative learning control laws. These algorithms were applied to adjust the level and timing of electrical stimulation, to achieve accurate arm tracking using the robot over the course of six iterations.