Skip to content
Evaluation of Correct Posture and ACL Injury Risk — Thesis Design project by YenkoDev

Evaluation of Correct Posture and ACL Injury Risk

Software as a Service

No

Category

Thesis Design

Clients

Mapua University

Techstack

PythonMediaPipeRaspberry PiOpenCV

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.