For people with knee osteoarthritis, a precise change to their walking pattern can relieve pain and slow the degeneration of their cartilage. Scott Uhlrich, Model Health's Chief Scientist, recently published a clinical trial in The Lancet Rheumatolgy (1), with collaborators at Stanford and NYU Langone Health.
Osteoarthritis is a leading cause of disability, affecting 21% of individuals over 402. The most commonly affected joint is the knee. There is no cure for osteoarthritis, so current treatments only address symptoms. Most patients will start with pain medications, proceed to joint injections, and ultimately receive a joint replacement when the pain becomes too debilitating. Researchers around the world have been working on way to slow, or even stop, the progression of osteoarthritis.
Improving biomechanics may be part of the answer. “We know that large forces transmitted through the knee during walking accelerate joint degeneration,” said Dr. Scott Uhlrich, who was a lead author on the study and is an Assistant Professor of Mechanical Engineering and Orthopaedic Surgery at the University of Utah and CSO of Model Health. Thus, reducing these joint forces is a target for new osteoarthritis treatments. One way to do this is to train people to walk in a subtly different way, called gait retraining.
This study trained people with osteoarthritis mainly on the medial side of their knee to walk with a new personalized foot angle — with their toes pointed more inwards or more outwards. The researchers first performed an in-depth analysis of each individual’s gait biomechanics and determined which new walking pattern would most effectively reduce the forces transmitted through the painful part of their knee.
“The gait analysis to personalize the intervention was a key part,” Uhlrich said, “not only were we able to find each individual’s most effective gait change, but we made sure we did not prescribe a new gait pattern that actually increased joint loading.”
Much of the past work in this area has given the same new gait pattern to everyone, but the researchers have shown that this one-size-fits-all approach can lead to a potentially harmful increase in joint forces for 10-44% of patients3.
Participants in the intervention group then learned their personalized gait pattern by walking in the lab with real-time feedback from a small vibrating device attached to their leg. After six lab visits, participants had learned their new walking pattern and were able to keep walking within 1° of their target angle over the course of the one-year study. The control group was taught to walk more consistently with their natural foot angle, so their knee loading was not expected to change.
After one year, the intervention group’s pain improved by more than the control group. The pain improvement was somewhere between what you’d expect from over-the-counter pain medications and narcotics4,5.
“One participant told me that she was thrilled to have less pain without having to wear a device or take a drug,” Uhlrich said.
The researchers also used MRI to determine how cartilage health was affected by gait retraining. The health of the control group’s cartilage declined over one year, as expected, but the intervention group did not see this same degeneration. Uhlrich said, “the MRI findings were a secondary part of the study and need further confirmation, but the potential to slow osteoarthritis with a non-invasive treatment like this is exciting.”
We know that remaining active is one of the best ways to manage osteoarthritis, and gait retraining may enable people to do this with less pain.
“I think it provides hope for people with osteoarthritis, that they can still go for a hike with their grandkids and keep doing many of the activities they enjoy.”
The main limitation of the study was that it required 12 visits to a university gait laboratory. Between the initial gait analysis and the biofeedback visits, retraining each participant’s gait required dozens of hours of analysis from engineers and $250,000 of research-grade biomechanical analysis equipment. “I get many emails every week of people asking where they can go to retrain their gait, but the approach we used in the study doesn’t scale,” Uhlrich said.
Digital health technology is one way to get this into the clinic. In the future, smartphone video–based gait analysis, like that developed by Model Health, could be used to identify which gait pattern is likely to help6,7. Then, wearable biofeedback devices, like those developed by Sage Motion, could be used for gait retraining8,9.
One of our goals at Model Health is to make the power of decades of biomechanics research easily accessible to physical therapists as they treat each unique patient. This is a good example where research-grade biomechanical assessment is needed to deliver the right treatment, but traditional motion capture is too cumbersome.
“When we started this study 10 years ago, it had to be done in the lab,” Uhlrich said, “It is exciting that the technology is now here to start moving this into the clinic.”
About Scott Uhlrich, Chief Science Officer at Model Health
Prior to joining the University of Utah as an Assistant Professor, Dr. Uhlrich earned his PhD in Mechanical Engineering at Stanford University and went on to direct research in the Stanford Human Performance Lab. At Stanford, he co-developed the OpenCap software with Dr. Antoine Falisse (CEO of Model Health), an academic platform for smartphone video-based biomechanical analysis that is used by thousands of researchers worldwide. These core algorithms became the foundation for the Model Health software. Dr. Uhlrich’s Movement Bioengineering Lab at the University of Utah develops digital health technologies aimed at improving rehabilitation outcomes for individuals recovering from stroke or ACL reconstruction and enhancing mobility for those with osteoarthritis or neuromuscular diseases.
References:
1. Uhlrich, S. D. et al. Personalised gait retraining for medial compartment knee osteoarthritis: a randomised controlled trial. The Lancet Rheumatology, Volume 0, Issue 0 (2025).
2. Ferrari, A. J. et al. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet 403, 2133–2161 (2024).
3. Uhlrich, S. D. et al. Personalization improves the biomechanical efficacy of foot progression angle modifications in individuals with medial knee osteoarthritis. J Biomech 144, (2022).
4. Corsinovi, L. et al. Efficacy of oxycodone/acetaminophen and codeine/acetaminophen vs. conventional therapy in elderly women with persistent, moderate to severe osteoarthritis-related pain. Arch Gerontol Geriatr 49, 378–382 (2009).
5. Kivitz, A., Eisen, G., Zhao, W. W., Bevirt, T. & Recker, D. P. Randomized placebo-controlled trial comparing efficacy and safety of valdecoxib with naproxen in patients with osteoarthritis. Journal of Family Practice 51, 530–537 (2002).
6. Uhlrich, S. D. et al. OpenCap: Human movement dynamics from smartphone videos. PLoS Comput Biol 19, (2023).
7. Boswell, M. A. et al. A neural network to predict the knee adduction moment in patients with osteoarthritis using anatomical landmarks obtainable from 2D video analysis. Osteoarthritis Cartilage 29, 346–356 (2021).
8. Xia, H., Charlton, J. M., Shull, P. B. & Hunt, M. A. Portable, automated foot progression angle gait modification via a proof-of-concept haptic feedback-sensorized shoe. J Biomech 107, (2020).
9. Charlton, J. M., Xia, H., Shull, P. B. & Hunt, M. A. Validity and reliability of a shoe-embedded sensor module for measuring foot progression angle during over-ground walking. J Biomech 89, 123–127 (2019).
