
Evaluation of Correct Posture and ACL Injury Risk
Software as a Service
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Thesis DesignClients
Techstack
Purpose
A Mapua University study using MediaPipe pose tracking to guide athletes through jump exercises in real time, evaluate its accuracy as a motion-sensing tool, and flag movement patterns that indicate elevated ACL injury risk.
Description
The system tracks body landmarks with MediaPipe on a Raspberry Pi during single-leg jumps, jump cuts, and depth jumps, providing real-time posture guidance for every repetition. Each jump is analyzed for indicators of anterior cruciate ligament injury risk, and the pose data is examined for recurring patterns that signal unsafe landing mechanics. The study also assessed MediaPipe's accuracy and reliability as a dedicated jump-posture assessment tool, supporting safer training methodologies.




