Gait analysis is a vital field in biomechanics, focusing on studying human walking patterns and movement. Traditional methods relied on visual observation, lacking accuracy and objectivity. Instrumented gait analysis improved measurements using specialized equipment like motion capture systems and wearable sensors, but had limitations due to cost, and markers or sensors interfering with natural movement. The field underwent a significant transformation with the advent of markerless pose estimation-based gait analysis, which harnessed computer vision methodologies to monitor human movement without the requirement for specialized equipment, delivering a cost-effective and easily accessible analysis in real-world environments. However, it still faces challenges, including limitations in the sagittal plane and reliance on computationally demanding models like OpenPose. This study introduced a novel frontal plane gait analysis approach using the lightweight MediaPipe Pose model and a single camera setup. The objective is to evaluate the feasibility, and accuracy of MediaPipe Pose by comparing it to the established 3D Vicon motion capture system. The proposed approach tracked body keypoints during gait, detected gait events based on ankle depth changes and vertical difference between left and right ankles, and calculated gait parameters. The findings demonstrated that MediaPipe Pose-based gait analysis showed promise for accurately analyzing gait parameters in the frontal plane with low mean absolute error (0.00–0.30). Combining this method with satellite technology enhances e-health by facilitating teleconsultations, remote diagnostics, and extending healthcare services to disaster-stricken or remote areas.
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