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Abstract(s)
Anterior Cruciate Ligament (ACL) injuries are among the most common and debilitating sports injuries, posing potential career-threatening consequences and carrying a high risk of re-injury. Movements involving sudden deceleration are particularly relevant in the context of ACL injuries, as deceleration actions are common high-impact tasks where non-contact ACL injuries typically occur. Accurate evaluation of ACL injuries is essential to determine when an athlete is ready to return to sport. Forward braking and backward acceleration is a functional test that mimics the abrupt deceleration common in various sports. This task replicates the real-life physical demands of abrupt decelerations and can simulate the stress on the knee encountered during such activities. Manual analysis of movement data can be time-consuming and prone to human error. An automated report framework offers several advantages in the context of motion capture and subsequent analysis, improving efficiency and consistency. Therefore, the primary objective of this work was to develop an automated framework specific to the biomechanical analysis of forward braking and backward acceleration in elite athletes. Using Qualisys Track Manager (QTM) and its Project Automation Framework (PAF) tools, two automation packages were created: one for marker-based and another for markerless motion capture data. These frameworks streamline the entire workflow, from motion capture to the generation of a customized biomechanical report. The frameworks automatically handle tasks such as model building, event detection, data processing, and report generation. The resulting report includes kinematic, kinetic, and electromyography (EMG) data specific to this task, and was designed in consultation with a professional who regularly uses this functional test. This automated approach eliminates the need for manual data processing, reducing errors and improving workflow efficiency. The final framework offers a practical tool for assessing this task in elite athletes, with applications in performance and injury evaluations.
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Keywords
Abrupt anterior/posterior deceleration Automatic reporting framework ACL injury Functional test