Can Iterative Learning Control be used in the Re-Education of Upper Limb Function Post Stroke?

Hughes A-M1, Burridge JH1, Freeman C2, Chappell P2, Lewin P2, Rogers E2

University of Southampton UK 1 School of Health Professions 2 School of Electronics and Computer Science

MethodIn 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.

IntroductionUK 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 patient’s 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 that patients are always working at the limit of their performance whilst motivated by their success.

Picture 3: Subject using robot with FES electrodes

EMG electrode signals

Modified 4 channel stimulator

Data projector

6 axis torque/force sensor

Brushless DC motor input signalsEncoders and Hall effect transducers

Goniometers

FES stmulation pulewidth demand

Limit switches

Emergency stop buttons

LED display

Data acquisition system 1

Data acquisition system 2

FES stimulation signals

ConclusionEarly 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.

ResultsInitial 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