Research project: Using functional electrical stimulation mediated by iterative learning control and robotics to improve arm movement for people with Multiple Sclerosis (PwMS)

This research continues work over the last 7 years where iterative learning control (ILC) algorithms have been used to control functional electrical stimulation (FES).  The algorithms used have been tested clinically in two small samples of stroke patients.  Recently FES mediated by ILC was applied to the triceps brachii and the anterior deltoid in stroke patients when using an Armeo 3D robot and a reduction of upper limb impairment was demonstrated following a period of training.  This study uses the same technology and model but will apply this to a small sample of Multiple Sclerosis patients to determine the feasibility of using this technology in this patient group.  Various reaching tasks with be performed with assistance from the Armeo 3D robot and FES in accordance with motor learning theory.

The project employs clinical and engineering research fellows and has global MS and neuro-rehabilitation specialist input from Belgium, Ireland and the UK who will work closely together to achieve the core project deliverables which involve integration of the system, movement analysis, FES controller implementation and testing, and clinical trials.  Further movement monitoring prior to and after the intervention will be assessed using Shimmer sensors which will record daily activity of the upper limb for 3-7 days.  A clinical research fellow will work on task/stimulation protocols and task progression for neuro-rehabilitation and an engineering intern will analyse data movement produced from the Shimmer sensors.