Omer Gan-El

To what extent can a sensorless, imaging-based AI system accurately identify biomechanical risk factors for ACL injuries while serving as an accessible feedback tool for everyday athletes?

Started June 23, 2025

Abstract or project description

The intersection of biomechanics, artificial intelligence, and applied mathematics is transforming how we prevent ACL and lower-body injuries. Rather than relying on expensive lab tools or wearable sensors, athletes can now receive accurate feedback through imaging-based motion analysis powered by AI and physics. These systems go beyond forming skeletal models and mirroring the person’s movement by now analyzing internal forces like torque and joint load to detect injury risk immediately. As studies have shown, this sensorless approach is both more reliable and accessible, paving the way for solutions that bring proactive injury prevention to athletes at all levels, anywhere and anytime.