Revolutionising Knee Care: Personalised Recovery with MAI Motion’s Marker-less Movement Analysis

Introduction: Why Personalised Knee Care Matters More Than Ever

Knee conditions such as osteoarthritis and meniscus tears affect millions of people worldwide, leading to pain, stiffness, and restricted movement. These problems can make everyday activities challenging and lower overall quality of life. As people increasingly search for treatments that address their unique needs, innovative technologies are transforming the field of knee care. One leading advancement is MAI Motion — a marker-less motion capture system that brings state-of-the-art movement analysis directly into clinics. In this article, we’ll explore how MAI Motion empowers clinicians to deliver personalised treatments, helping patients achieve a quicker, more comfortable recovery.

From Traditional to Digital: The Evolution of Knee Treatment

For years, knee assessments leaned heavily on visual observation and patient reporting. While helpful, these methods often miss the finer details of how joints move, resulting in standardised treatments that may not target each person’s specific challenges.

Digital health innovations like MAI Motion are changing this. Using marker-less technology, MAI Motion eliminates the need for cumbersome sensors or sticky markers. Patients can move naturally while the system records their knee movement in real time. This approach captures precise joint data without making the assessment process more complex or tiring. For example, patients only need to perform three repetitions of a movement instead of five to achieve reliable results, making assessments faster and more comfortable. This shift has made knee care more accurate, efficient, and focused on the real needs of patients.

How MAI Motion Works: Advanced Movement Analysis Made Simple

MAI Motion uses sophisticated algorithms to analyse knee movement seamlessly and precisely — all without attaching markers or wires. This gives patients the freedom to move as they normally would, which is crucial for detecting genuine movement patterns.

The system collects comprehensive data on joint angles, muscle activity, and movement symmetry. With this information, clinicians can accurately identify abnormalities and better understand each patient’s condition. Research shows that marker-less motion capture yields biomechanical insights that reflect natural movement, without the interference of physical markers. By streamlining protocols — such as using just three repetitions for functional tests — MAI Motion reduces fatigue without sacrificing data quality. This keeps assessments efficient for both patients and clinicians while ensuring that valuable information is never lost.

Targeting Osteoarthritis and Meniscus Tears with Precision

Conditions like knee osteoarthritis and meniscus tears impact the knee joint in distinct ways, leading to instability, discomfort, and reduced mobility. MAI Motion allows clinicians to spot subtle changes in movement that might otherwise go undetected.

The system can, for instance, identify if someone is subconsciously changing the way they walk to compensate for a meniscus injury, or if certain motions put extra strain on the knee due to osteoarthritis. Even small variations in the knee’s range of motion — just a few degrees — can reveal early signs of joint problems or track progress throughout rehabilitation . With this precise insight, clinicians are able to deliver treatment plans that are truly tailored to each patient, rather than relying on generic approaches. This also makes it much easier to monitor recovery, adapt the plan as needed, and help patients return to normal activities faster.

Putting Technology into Practice: Better Care, Happier Patients

MAI Motion brings practical improvements to both clinics and patients. Clinicians benefit from clearer, data-driven assessments, which allow them to create highly targeted rehabilitation plans. On the patient side, real-time feedback during exercises encourages active participation in recovery, boosting both motivation and outcomes.

A major advantage is the comfort and convenience MAI Motion offers. The marker-less, less strenuous assessment is ideal for those with pain or limited endurance, making rehabilitation more accessible for everyone. By focusing care on each person’s specific needs and providing clear guidance, this technology not only speeds up recovery but also empowers patients to take charge of their knee health.

Looking Ahead: The Future of Personalised Knee Rehabilitation

The integration of advanced technology like MAI Motion is transforming the way knee conditions are diagnosed and treated. By providing clinicians with detailed, patient-specific movement data, it enhances the effectiveness of interventions for osteoarthritis, meniscus tears, and other knee issues.

As digital health tools continue to evolve, assessments will only become easier, faster, and more precise. Adopting these innovations stands to benefit both healthcare providers and patients, ushering in an era of truly personalised, effective knee rehabilitation.

Conclusion: Embracing Innovation for Stronger, Healthier Knees

MAI Motion’s marker-less motion capture system represents a major leap forward in personalised knee care. By combining precise movement analysis with convenient, patient-friendly assessments, it enables clinicians to create treatments tailored to each individual’s needs. For patients, this means greater comfort, more effective rehabilitation, and a clearer path to better mobility.

Looking to the future, integrating digital health technologies like MAI Motion into everyday care will be crucial for delivering the personalised support patients deserve. By embracing these advancements, we’re setting a new standard for knee health — one that leads to stronger joints, greater confidence, and an improved quality of life for all.

References

  • Armstrong, K., Wen, Y., Zhang, L., Ye, X., & Lee, P. (2022). Novel Clinical Applications of Marker-less Motion Capture as a Low-cost Human Motion Analysis Method in the Detection and Treatment of Knee Osteoarthritis. Journal of Arthritis, 11. https://doi.org/10.4172/2167-7921.2022.11.053
  • Armstrong, K., Zhang, L., Wen, Y., Willmott, A. P., Lee, P., & Ye, X. (2024). A marker-less human motion analysis system for motion-based biomarker identification and quantification in knee disorders. Frontiers in Digital Health. https://doi.org/10.3389/fdgth.2024.1324511
  • Wen, Y., Verma, T., Whitehead, J. P., & Lee, P. (2025). Empirical Validation of a Streamlined Three-Repetition Sit-to-Stand Protocol Using MAI Motion. Applied Sciences, 15(10), 5688. https://doi.org/10.3390/app15105688