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New technique to help stroke patients re-learn movement

16.06.2005


A technique derived from industry could help stroke patients to move again.



Researchers at the University of Southampton’s School of Electronics and Computer Science (ECS) and the School of Health Professions & Rehabilitation Sciences have begun working on a project to establish whether iterative learning control techniques can help a stroke patient to re-learn movement.

Dr Jane Burridge from the School of Health Professions & Rehabilitation Sciences who is leading the research commented: ‘As far as we know, nobody has tried using iterative learning control to help people who have had a stroke to move again. It is a great example of how new techniques in control theory – this one is normally used for industrial robots – can be applied to challenges in rehabilitation.’


The team will look at how electrical stimulation to contract appropriate muscles through electrodes attached to the skin can be controlled to enable stroke patients to successfully perform tasks. The patient will attempt to track a moving target over a two dimensional plane by moving a joy-stick. The patient’s movement will be measured to detect the tracking error and learning algorithms applied to adjust the level and timing of stimulation so that the error is corrected. The ultimate aim is that through repetition, voluntary movement will improve, thus gradually reducing the need for artificial stimulation.

Dr Paul Lewin commented: ‘This is a very challenging project as it is the first time in Europe that this technology has been applied to humans. With robots, behaviour is entirely predictable, you can make them perform a task perfectly every time. People often reach a natural plateau in their performance, but if you can get them to repeat moves using certain tasks, they have a much better chance of recovery.’

The team has been awarded £379,946 by the Engineering and Physical Sciences Research Council (EPSRC) to conduct this research over a three-year period.

Joyce Lewis | alfa
Further information:
http://www.soton.ac.uk

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