Strengths and Weaknesses of 3D Pose Estimation and Inertial Motion Capture System for Movement Therapy
This work addresses the need for non-invasive motion analysis in clinical settings, but it is incremental as it evaluates an existing method on new data without introducing novel techniques.
The study compared the accuracy of the 3D pose estimation method MeTrabs with the inertial sensor system MTw Awinda for movement therapy exercises, finding that mean and median deviations for some joint angles were below 5°, but maximum deviations reached up to 50° for problematic joints like the elbow.
3D pose estimation offers the opportunity for fast, non-invasive, and accurate motion analysis. This is of special interest also for clinical use. Currently, motion capture systems are used, as they offer robust and precise data acquisition, which is essential in the case of clinical applications. In this study, we investigate the accuracy of the state-of-the-art 3D position estimation approach MeTrabs, compared to the established inertial sensor system MTw Awinda for specific motion exercises. The study uses and provides an evaluation dataset of parallel recordings from 10 subjects during various movement therapy exercises. The information from the Awinda system and the frames for monocular pose estimation are synchronized. For the comparison, clinically relevant parameters for joint angles of ankle, knee, back, and elbow flexion-extension were estimated and evaluated using mean, median, and maximum deviation between the calculated joint angles for the different exercises, camera positions, and clothing items. The results of the analysis indicate that the mean and median deviations can be kept below 5° for some of the studied angles. These joints could be considered for medical applications even considering the maximum deviations of 15°. However, caution should be applied to certain particularly problematic joints. In particular, elbow flexions, which showed high maximum deviations of up to 50° in our analysis. Furthermore, the type of exercise plays a crucial role in the reliable and safe application of the 3D position estimation method. For example, all joint angles showed a significant deterioration in performance during exercises near the ground.