Title: The feasibility of using BiofEedback to reduce Pain in people with Knee Osteoarthritis (BEPKO)
Funder: Department of Health and Social Care

Abstract: Research has consistently demonstrated that individuals with knee osteoarthritis (KOA) walk with increased co-contraction (simultaneous activation) of the hamstrings and quadriceps. This muscle pattern will increase the compressive loading at the knee joint and could be a key driver of KOA progression. Co-contraction is not addressed in current physiotherapy management of KOA and is therefore a novel treatment target which requires further investigation. This project will build on previous research by the applicants demonstrating the potential clinical benefit of reducing co-contraction in patients with KOA and also on proof-of-concept work which demonstrated the possibility of using biofeedback to enable patients to downregulate their knee muscle activity. We propose to refine a proof-of-concept intervention for reducing co-contraction in patients with KOA. This intervention will utilise Electromyography (EMG) technology, in which small skin-mounted electrodes measure electrical activity produced during muscle contraction. Although EMG technology has been used to develop biofeedback applications for conditions such as neck pain and fibromyalgia, a biofeedback application for KOA does not exist. Therefore, through patient/physiotherapist consultation we identified four components of a biofeedback intervention: incremental training activities (ITAs), easy-to-understand biofeedback software, instructional videos and a home practice component. In our proposed intervention, ITAs will increase in complexity, enabling a patient to gradually relearn the coordination required to walk with reduced muscle co-contraction. We have already developed a system which allows us to select individual ITAs from an understanding of how a patient s muscle patterns compare to those of a healthy person during walking. Our intervention is therefore personalised to individual physiology (EMG patterns during walking) but yet will still be sufficiently simple to be delivered in routine NHS clinical practice. Over the course of the project we will perform a number of cycles of intervention testing, user consultation and intervention refinement. User consultation will be achieved through co-design workshops and individual interviews and we will use thematic analysis to develop specific criteria which will inform subsequent improvements of the intervention. In addition, we will collect EMG data from a cohort of n=50 healthy subjects across a range of ITAs which will facilitate the development of biofeedback software. This will provide patients with visual information on how their muscle patterns compare to those of a healthy person. We will also work with an animator to develop short instructional videos which will provide patients with unambiguous instruction on how to down-regulate muscle activity. Once the study is complete, we will apply for further funding to run a feasibility study to test the potential clinical effectiveness of our intervention. Positive outcomes from a feasibility study would pave the way for a large scale RCT which could directly impact on the way in which KOA is managed by physiotherapists. Whereas current clinical management models focus on muscle strengthening and/or aerobic exercise, our proposed biofeedback intervention will provide individuals with the skills to sense and influence their own muscle patterns. This approach will therefore promote long-term self-management of KOA.

Lay abstract: Previous research shows that people with knee osteoarthritis (KOA) over tighten their knee muscles when they walk. This muscle pattern increases the pressure on the knee joint, which may cause the joint to degenerate more rapidly than it would in a healthy person. Current physiotherapy approaches for managing KOA typically involve general muscle strengthening and exercise, and therefore are not aimed at reducing over tightening of the knee muscles. Therefore, we propose a new treatment for KOA which is aimed at teaching patients to change the way they use their knee muscles during walking. Our new treatment uses a technique known as electromyography (EMG) in which sensors, placed on the skin, are used to measure how hard muscles work during activities, such as walking. Patients can see this muscle activity on easy-to-understand computer software. We can then give specific exercises and instructions (using appropriate imagery) on how to contract the muscles differently to reduce pressure on the knee joints. We have already worked with patients and physiotherapists, and have identified four key parts of the intervention. These include 1) computer software to show muscle patterns, 2) a set of training activities which will allow patients to gradually learn to improve their muscle coordination during walking, 3) instructional videos to provide patients with clear visual instructions on how to reduce muscle activity and 4) a home practice programme. In this work we will refine the four components of the intervention by working closely with patients with KOA and interviewing them to understand their views on how it can be improved. This will allow us to optimise the new treatment. Once this study is complete, we will apply for further funding to run a feasibility study to understand the potential clinical benefit of our new treatment.

Research activity codes: 5.7 PHYSICAL
Health categories: MUSCULOSKELETAL