Enhancing Chronic Pain Management with MAI Motion’s Reduced Repetition Approach

Introduction

Chronic pain affects millions of people worldwide, turning simple daily tasks into ongoing challenges. Both patients and healthcare providers are constantly searching for better ways to manage symptoms, especially when it comes to movement—a key factor in both understanding and treating chronic pain. Traditional movement assessments require patients to repeat specific actions multiple times, which can be tiring and sometimes results in inconsistent data. These challenges often make it harder for clinicians to make the best treatment decisions. Thankfully, technology is offering new hope. With MAI Motion’s markerless motion capture system, detailed movement analysis can be done with fewer repetitions, reducing fatigue without sacrificing accuracy. This innovation is paving the way for more personalized and effective management of chronic pain.

The Problem with Traditional Movement Assessments

Movement assessment is critical when managing chronic pain, especially for conditions that affect muscles and joints. Traditionally, assessments have asked patients to repeat the same action—like getting up from a chair—several times in a row. While this repeated approach can provide comprehensive data, it is often exhausting for those already dealing with pain or fatigue, making them less likely to participate fully. Overexertion during these tests can even skew the results, making it difficult to design effective treatments.

Markerless motion capture technology represents a welcome shift. Instead of attaching uncomfortable sensors to the body, these systems use cameras and intelligent software to track movements naturally and comfortably. The goal of reducing repetition is straightforward: gather all the information clinicians need, without overburdening the patient. Recent research shows that reliable and useful information can still be obtained from fewer repetitions. Markerless technology, by capturing natural movement, gives clinicians richer, more authentic insights into a patient’s abilities.

What Is MAI Motion’s Reduced Repetition Protocol?

MAI Motion is a next-generation system that records movement data without the need for any markers or sensors attached to the body. One of its commonly used tests is the sit-to-stand maneuver—a simple but powerful indicator of mobility and strength. While traditional testing often requires five or more repetitions, MAI Motion delivers comparable results with just three.

Studies have demonstrated that this reduced repetition protocol is just as effective as the longer, traditional approach. Key measures such as joint angles and the steadiness of movements—how consistently someone moves each time—remain reliable with only three repetitions. Data like the “coefficient of variation” (which reflects movement consistency) and “mean difference” (showing the average variation between tests) stay low, confirming that the results are both reliable and meaningful. Because MAI Motion is completely markerless, it also avoids the discomfort or awkwardness that can come with older systems, ensuring that movement is measured as naturally as possible.

Why This Matters for People Living with Chronic Pain

For those living with chronic pain, every bit of effort counts. The fatigue from repetitive movement testing can increase discomfort and reduce willingness to participate, leading to fewer and less useful assessments. By minimizing the physical strain, MAI Motion keeps patients comfortable and engaged, helping them stick with their rehabilitation plans and get more accurate assessments over time.

This detailed, patient-friendly approach empowers healthcare professionals to tailor therapy and rehabilitation programs to each individual’s unique needs. It is especially valuable for older adults or those with frailty, where excessive activity might not be practical or safe. Ultimately, this smarter method of assessment can help patients regain mobility and improve their quality of life by making the process less intimidating and more effective.

Looking Ahead: The Future of Motion Analysis in Pain Management

MAI Motion’s reduced repetition protocol is more than just a minor update—it has the potential to change how chronic pain is assessed and managed. Since the system is markerless and easy to use, assessments can even be done outside of the clinic, including at home via remote monitoring. This opens the door for continual progress tracking in real-world settings, which is essential for managing persistent conditions.

Shorter assessments also make clinics run more smoothly, saving time for both patients and providers and making advanced diagnostics available to more people. As healthcare moves towards more personalized and digital solutions, tools like MAI Motion are shaping a future where chronic pain care is more efficient, more accurate, and more centered on the needs of real people.

Conclusion

Reducing the number of repetitions in movement analysis marks a meaningful breakthrough in chronic pain care. MAI Motion offers a smart, patient-friendly solution that achieves both comfort and accuracy. By lowering fatigue while still delivering top-quality data, it enhances the experience for patients and supports better clinical decision-making. As this technology becomes more widespread, it promises to help countless people with chronic pain lead fuller, more active lives.

References

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
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, 10.3389/fdgth.2024.1324511