Nestled next to Stanford University’s physical therapy clinic, the human performance lab is a hub for biomechanical analyses, often requested by orthopedic surgeons for athletes with recurring injuries. However, these analyses, previously laborious and time-consuming, are now being revolutionized with the introduction of a motion-capture app developed by lab’s director of research, Scott Uhlrich, PhD, and his team of bioengineers.
This groundbreaking application, known as OpenCap, utilizes smartphone footage, artificial intelligence (AI), and computational biomechanical modeling to rapidly quantify human movement. The app’s efficiency and accessibility could prove instrumental in designing proactive interventions for mobility issues, expediting recovery, and filling vast knowledge gaps within human mobility research.
OpenCap operates by uploading footage of human movement, recorded by two smartphones, to the cloud. An algorithm then identifies specific points on the body through computer vision algorithms, a form of AI that interprets visual data, in this instance, a person’s pose. Following this, the app quantifies the body’s movement in three-dimensional space, providing valuable insights into the angle of a joint, the stretch in a tendon, or the force transferred through the joints.
Compared to the conventional analysis approach, which requires specialized expertise and costs around $150,000, OpenCap offers a free and user-friendly alternative. This democratization of human movement analysis could significantly improve outcomes for patients globally.
Current research on human mobility has many mysteries yet to be unraveled, such as when balance begins to degrade in aging adults, the progression of sports injuries or degenerative joint diseases like arthritis. OpenCap could be the key to unlocking these mysteries, allowing for more extensive studies due to its cost-effectiveness and ease of use.
The app has already been adopted by approximately 2600 researchers worldwide, many of whom had never created a dynamic simulation before. Its potential applications are vast, from studying hamstring strain injuries during sprinting to building new tools for identifying injury risks or measuring balance. Indeed, movement could soon be established as a biomarker, with clinicians using the app to assess disease risk and progression or the risk of falling.
As an underdog in the world of biomechanical analysis, OpenCap is now sprinting ahead, taking giant leaps for both researchers and patients. Its potential to revolutionize the field is enormous, and I’m excited to see how it will continue to shape our understanding of human mobility.
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