New research partnership aims to use AI-based movement analysis to identify knee osteoarthritis risks earlier and guide patients towards the right level of care. Knee osteoarthritis is one of the most common causes of long-term knee pain, stiffness and reduced mobility, especially among older adults. However, many people only seek treatment after their symptoms have already become more serious.
A new collaboration between Singapore and Hong Kong hopes to change that by bringing earlier assessment and screening closer to the community.
The Yong Loo Lin School of Medicine at the National University of Singapore and The Hong Kong Polytechnic University are working together on an artificial intelligence-enabled approach that could help identify people at risk of knee osteoarthritis before they need specialist hospital treatment.
A New Partnership Focused on Community Musculoskeletal Care
The National University of Singapore's Department of Orthopaedic Surgery and the Department of Biomedical Engineering at The Hong Kong Polytechnic University have signed a memorandum of understanding to support joint research in community-based musculoskeletal care.
The partnership will centre around a programme called JointCare, which is designed to improve how knee osteoarthritis is assessed, managed and referred within local community settings.
Rather than relying only on hospital visits and specialist consultations, the initiative aims to help healthcare providers identify people who may benefit from early intervention, exercise guidance or community rehabilitation programmes.
Using AI to Understand How People Move
One of the more interesting parts of the JointCare programme is its use of AI-enabled movement profiling.
The system is being developed to assess lower-limb movement patterns linked to knee osteoarthritis. It uses a label-free approach, meaning patients may not need to wear complex sensors or tracking devices during the assessment.
By analysing how a person walks, bends, moves their knees or shifts body weight, the technology may help detect movement patterns that could indicate knee osteoarthritis risks or early functional issues.
This movement analysis will be used together with structured questionnaires, allowing healthcare teams to assess symptoms, mobility concerns and risk factors in a more organised way.
Helping Patients Receive the Right Care Earlier
The broader goal is not simply to identify knee osteoarthritis. It is also about helping patients receive care at the most appropriate level.
Some individuals may be suitable for community-based support, such as physiotherapy, exercise programmes, weight management advice or pain-management guidance. Others with more serious symptoms may need faster referral to specialist orthopaedic services.
By separating lower-risk and higher-risk cases earlier, JointCare could potentially reduce unnecessary hospital referrals while ensuring more urgent cases are reviewed without delay.
This may also help relieve pressure on hospitals and specialist clinics, where waiting times can become longer when large numbers of patients are referred for conditions that could be managed safely in the community.
Pilot Programme Set to Begin in Singapore
The project is expected to begin with an early proof-of-concept pilot in Boon Lay, Singapore, during the fourth quarter.
The initial phase will test how well the AI-enabled assessment works in a real community environment. Researchers will evaluate the feasibility of the process, the reliability of the results and how easily the workflow can be integrated into community healthcare services.
The pilot will also help the team identify areas for improvement before expanding the programme to more locations.
Over time, JointCare is expected to be introduced progressively across communities in western Singapore. The two universities will also explore opportunities for wider international research collaboration, including possible future work in Hong Kong.
AI Is Becoming More Common in Osteoarthritis Research
The JointCare programme is part of a wider international trend where researchers are looking at how AI can support earlier diagnosis, prediction and care planning for osteoarthritis.
In South Korea, for example, researchers previously developed an AI model that could estimate whether a person with osteoarthritis in one knee might later develop the same condition in the other knee.
These types of projects show how AI may become increasingly useful in identifying risks before symptoms become more severe or mobility declines further.
Community Care Is Becoming a Bigger Focus
NUS Medicine has also been expanding its interest in bringing healthcare research and preventive services closer to local communities.
In 2023, the university established the Centre for Innovation and Precision Eye Health, which focuses on improving eye healthcare through community-level initiatives.
The new knee osteoarthritis project follows a similar direction: use technology, research and early screening to help people receive support before their health conditions become more complicated.
Final Thoughts
The Singapore-Hong Kong collaboration highlights how AI may help shift knee osteoarthritis care from a mainly hospital-based model towards earlier support within the community.
By combining movement analysis, structured screening and better triage, JointCare could make it easier to identify patients who need specialist attention while helping others receive timely care closer to home. For people living with early knee discomfort, this kind of approach could eventually mean faster guidance, better prevention and a smoother path to the right treatment.
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