Research Revealed, S01E04: How Artificial Intelligence is helping people manage back pain

By David Proctor - 10 January 2024

The fourth episode of Research Revealed looks at how Artificial Intelligence (AI) is helping people suffering with low back pain manage their condition.

Previously, episode one highlighted RGU’s School of Pharmacy and Life Sciences, focusing on a research project that aims to tackle the global issue of a lack of safe, reliable drinking water.

For episode two, researchers from Gray's School of Art and the School of Applied Social Studies explored the impact that Brexit and lockdowns have had on people in the UK.

Episode three explored a project from the School of Nursing, Midwifery & Paramedic Practice related to tackling child poverty in the North East and further afield.

Now, Research Revealed is turning its attention to selfBACK, which aims to harness digital technology to change the self-management of low back pain. Researchers from the Schools of Health Sciences and Computing have been explaining their role in the project. 

The World Health Organisation estimates that low back pain causes discomfort for millions of people across Europe and can have a significant cost to the continent’s various economies.

Researchers from RGU have made a crucial contribution to a solution which incorporates expertise from the disciplines of health and computing.

RGU is one of the partners in the selfBACK consortium, an international group of academics and industry experts aiming to transform the self-management of low back pain through digital technology.

Professor Kay Cooper, Associate Dean for Research in the School of Health Sciences and Professor Nirmalie Wiratunga, Associate Dean for Research in the School of Computing, helped developed the of activity recognition algorithms and the development of theory-backed digital intervention approaches.

Being physically active, doing specific exercises and being educated about self-management of low back pain are three vital components to successfully managing the problem with selfBACK including this important trio of elements.

The decision support system provides patients with a personalised self management plan consisting of physical activity, exercised and self-management advice. It is designed to complement any treatment and advice provided by a healthcare professional such as a GP or physiotherapist. It uses an AI methodology called Case-Based Reasoning (CBR) to recommend self-management plans that are tailored to an individual person’s needs. Sensor data is continuously read from a wearable device worn by the user, and the user’s activities are recognised in real time.

Guidelines for low back pain recommend that patients should not be sedentary for long periods of time. If the selfBACK system detects continuous periods of sedentary behaviour, a notification is given to alert the user.

At the end of the day, a daily activity profile is also generated which summarises all activities a user does. The information in this daily profile also includes the durations of activities and the number of steps taken while walking or running.

Kay said: “It was based on the evidence for management of low back pain, which has three main arms, and that is being physically active, doing specific exercises, and receiving education around self-management strategies. The selfBACK app incorporates all of these three components.

“This was a very interdisciplinary project because it brought across all the different project partners, it brought together people from a health and exercise background, along with people from a computing science background and also people from industry for the app to be developed into an actual product.”

Nirmalie added: “It's fair to say that the computing people are mainly working with the algorithm side, while the health scientists, they have a responsibility also to the human side. That kind of interactive approach was, I would say, a real advantage to have for this project by bringing two disciplines together.

“One of the things that self-back wanted was specializing in predictive monitoring, and so our research work fit into that particular package called predictive monitoring. So, everything to do with keeping track of what an end-user or a person is doing.”

RGU is a member of the selfBACK consortium which includes the Norwegian University of Science and Technology, Syddansk Universitet, University of Glasgow, Denmark’s National Research Centre for the Working Environment, Trade Expansion and Health Leads.

The selfBACK project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No. 689043

More recently, selfBACK was named as one of seven digital apps recommended for use as part of draft guidance by the National Institute for Health and Care Excellence (Nice) to help people with lower back pain.

Nice’s draft recommendation of the digital platforms aims to reduce inequalities in accessing musculoskeletal services across the country. Other benefits envisaged include reducing waiting lists, the number of GP and physiotherapy appointments, the use of medication and the potential need for surgery.

Professor Kay Cooper

RGU’s research is focused on making a positive impact on the world by applying collaborative interdisciplinary research expertise to improve quality of life, deliver innovative solutions for business and industry, and contribute towards global sustainability.

Its research strategy is focused on growing the quality and impact of its research excellence around four key themes - inclusive and creative societies; the environment, energy and sustainability; health and wellbeing; and living in a digital world.

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