Efficacy of Iterative Learning Control for Stroke Rehabilitation

Strokes affect between 174 and 216 people per 100 000 population in the UK each year. Approximately two-thirds of patients in England will survive their stroke; of the 900 000 stroke survivors, 50 per cent are disabled and dependent. Although a high number of patients have upper limb impairments initially poststroke, despite therapy, very few regain useful arm movement regarded as being an important factor affecting independence. Upper limb function is clearly a major problem, which current treatment approaches are not solving.If the capacity of health and social services is to meet future demand, new approaches to rehabilitation are required. Evidence supports the use of electrical stimulation (ES) to reduce arm impairments following stroke, but until now, techniques have not allowed performance related feedback – as has been demonstrated with robotic devices. To promote voluntary activity using ES, the stimulation must be adjusted in response to the users’ performance; providing only the minimum level of stimulation needed to assist the patient in performing the task to a high level of accuracy