Evaluation of Correct Posture and ACL Injury Risk

Clients

Techstack

Purpose

The movements that blow out an athlete's knee happen in a fraction of a second and are nearly impossible to judge with the naked eye. A research team wanted to find out whether an ordinary camera and motion tracking could watch an athlete jump and flag the landing patterns that signal a high risk of ACL injury.

Description

We built a system that tracks an athlete's body in real time through single-leg jumps, jump cuts, and depth jumps, coaching posture on every repetition and analyzing each landing for the mechanics tied to knee-ligament injuries. The study also measured how accurate and reliable camera-based motion tracking is as a standalone assessment tool, with an eye toward safer training. Reading human movement well enough to catch injury risk as it happens is exactly the kind of hard computer-vision work we take on.