This project presents a computer vision–based system for measuring and analyzing patients responses to balance perturbations during rehabilitation. The system uses a GoPro camera mounted on a moving cart to capture patients from a frontal view while walking. Using skeletal keypoint detection, image segmentation, and homography-based transformations, the system identifies recovery steps and calculates their length in real-world units as an indicator of patient stability. The system was evaluated against ground-truth data collected with a laboratory Motion Capture (MoCap) system. Results demonstrate its potential as an automated tool for stability assessment and rehabilitation monitoring in patients with balance impairments.