Smart technology cuts physiotherapy waiting times

NewsGuard 100/100 Score

Technology with the potential to help cut physiotherapy waiting times has been unveiled by the University of Abertay Dundee.

Researchers in Abertay's School of Computing and Creative Technologies have developed an intelligent exoskeleton that can be programmed to remember and repeat specific limb movements.

The NeXOS system will enable physiotherapists to devise exercise programmes customized to the individual needs of any patient with lower limb problems. As well as victims of leg or spinal cord injuries, this could include stroke patients.

Such patients need regular exercise of the affected limb, to keep muscles in trim and prevent the loss of bone mineral density. There are currently 28,000 people on waiting lists for physiotherapy in Scotland.

NeXOS can exercise patients' legs exactly as the physiotherapist wishes, but without the need for the physiotherapist to be present in person. Many more patients could be treated per therapist, leading to potentially big cuts in waiting times.

As well as providing exercise tailored precisely to each patient's requirements, NeXOS can also monitor how well each patient is responding and send data back to the physiotherapist, using the internet if necessary.

This opens up the possibility of NeXOS being used away from conventional clinics, perhaps being installed in local gyms and sports centres or even patients' own homes. Patients would be able to exercise almost anytime, anywhere, and physiotherapists would be able to monitor progress and adjust settings accordingly by remote control.

Abertay researchers led by Professor David Bradley developed NeXOS in conjunction with the Universities of Sheffield and Sheffield Hallam, and Barnsley Hospital NHS Foundation Trust. The project was supported by the Department of Health through its NEAT (New and Emerging Applications of Technology) programme.

NeXOS uses pneumatics technology because of its ability to be programmed to variable degrees of power and resistance. Power is needed to move immobile limbs, but gradually increasing resistance is needed to encourage muscles to regain their strength.

The device was originally intended to be an intelligent exo-skeleton that could improve the mobility of people with permanent lower limb disabilities, but Professor Bradley and his colleagues quickly realized that the basic concept could be modified into a rehabilitation tool for temporary lower limb problems as well.

Researchers videotaped dozens of physiotherapy sessions, recording exactly how the feet and legs of patients were being manipulated, and converting the movements into a range of mathematical models describing the movements in three dimensions.

These formulae were then used to programme the exoskeleton with the variety of motions it needs to work. The result is that a physiotherapist can adjust the range, speed and direction of each movement, ensuring that the patient is getting treatment appropriate to his or her condition.

As well as academics at the three universities involved, practising physiotherapists, clinicians, engineers, mathematicians, health administrators and patients were all involved in brainstorming and analysing the concept. Further research is planned on ways in which therapists could use the technology more effectively, and the Abertay-led team is now looking to stage further trials in conjunction with a potential manufacturer.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
New machine learning model achieves breakthrough in heart disease prediction with over 95% accuracy