Strengths and Weaknesses of 3D Pose Estimation and Inertial Motion
  Capture System for Movement Therapy
Shawan Mohammed Hannah Siebers Ted Preuß
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{\deg} for some of the
studied angles. These joints could be considered for medical applications even
considering the maximum deviations of 15{\deg}. However, caution should be
applied to certain particularly problematic joints. In particular, elbow
flexions, which showed high maximum deviations of up to 50{\deg} 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.