1. Can Iterative Learning Control be used in the Re-Education of Upper Limb Function Post Stroke? Hughes A-M 1, Burridge JH 1, Freeman C 2, Chappell P 2, Lewin P 2, Rogers E 2 University of Southampton UK 1 School of Health Professions 2 School of Electronics and Computer Science Method In order to investigate the feasibility of using ILC, mediated by electrical stimulation with patients, a model is first being created with 10 unimpaired subjects. The initial aim is to identify activation patterns using surface electromyography during nine reaching tasks. The tasks are in three directions, at three speeds and three distances. This will inform which muscles we need to apply stimulation to and when. The second part looks at creating a model, moving the arm with and without stimulation and then using ILC to control the FES. References: Intercollegiate working Party for Stroke 2004, National Clinical Guidelines for Stroke, Royal College of Physicians, London. De Kroon, J. R., van der Lee, J. H., Izerman, M. J. & Lankhorst, G. J. 2002, "Therapeutic electrical stimulation to improve motor control and functional abilities of the upper extremity after stroke: a systematic review", Clinical Rehabilitation, vol. 16, pp. 350-360. Burridge, J. H. & Ladouceur, M. 2001, "Clinical and therapeutic applications of neuromuscular stimulation: A review of current use and speculation into future developments", Neuromodulation, vol. 4, no. 4, pp. 147-154. Introduction UK Stroke Guidelines suggest Robot-assisted movement therapy should be considered as an adjunct to conventional therapy for chronic patients with a deficit in arm function (Intercollegiate working Party for Stroke, 2004). A body of evidence also exists to support the use of functional electrical stimulation (FES) to improve motor control (De Kroon et al. 2002), (Burridge & Ladouceur 2001). Our interdisciplinary study funded by EPSRC (EP/C51873X/1) aims to investigate the feasibility of using Iterative Learning Control (ILC) mediated by FES for upper limb rehabilitation post stroke. The objective is to extend the patients ability to perform a 2D tracking task with their arm supported by the robot. Iterative learning control reduces the error between the actual and desired trajectory during repeated performances of a tracking task by adjusting the level of FES. Levels of FES can be reduced, or trajectory difficulty increased, to ensure t hat patients are always working at the limit of their performance whilst motivated by their success. Picture 3: Subject using robot with FES electrodes Conclusion Early results suggest Iterative Learning Control mediated by FES can be used to enable normal subjects to accurately track a trajectory within six iterations. Future Work To investigate whether stroke subjects can use voluntary activation assisted by ILC mediated by FES to accurately track a trajectory. If successful, the concept could be applied to other neurological conditions, such as cerebral palsy and incomplete spinal cord injury. Results Initial results suggest: i)that individual subjects have different activation patterns for three repeats of the same trajectory. ii)triceps and anterior deltoid appear to be active during reach, upper trapezius activity is lowest, whereas middle and lower trapezius activity is highest at maximum reach. Picture 2: Subject using robot with EMG electrodes Picture 1: Diagram of robot set up Picture 4: EMGs for 1 trajectory