Reconstruction of skeletal movement using skin markers: comparative assessment of bone pose estimators

Background: The assessment of the accuracy of the pose estimation of human bones and
consequent joint kinematics is of primary relevance in human movement analysis. This study
evaluated the performance of selected pose estimators in reducing the effects of instrumental
errors, soft tissue artifacts and anatomical landmark mislocations occurring at the thigh on the
determination of the knee kinematics.
Methods: The pattern of a typical knee flexion-extension during a gait cycle was fed into a knee
model which generated a six-components knee kinematics and relevant marker trajectories. The
marker trajectories were corrupted with both instrumental noise and soft tissue artifacts. Two
different cluster configurations (4 and 12-marker cluster) were investigated. Four selected pose
estimators, a Geometrical method, a SVD-based method, and the Pointer Cluster Technique in the
optimized and non optimized version, were analyzed. The estimated knee kinematics were
compared to the nominal kinematics in order to evaluate the accuracy of the selected pose
estimators.
Results: Results have shown that optimal pose estimators perform better than traditional
geometric pose estimators when soft tissue artifacts are present. The use of redundant markers
improved in some cases the estimation of the dynamics of the kinematics patterns, while it does
not reduce the offsets from the nominal kinematics curves. Overall, the best performance was
obtained by the SVD-based pose estimator, while the performance of the PCT pose estimator in
its optimal version was not satisfactory. However, the knee kinematics errors reached 5 deg for
rotations and 10 mm for translations).
Conclusion: Given the favorable experimental conditions of this study (soft tissue artifacts
determined from a young, healthy and non overweight subject), the errors found in estimating the
knee kinematics have to be considered unsatisfactory even if the best performing pose estimator
is used. Therefore, it is the authors' opinion that the movement analysis research community
should make additional efforts in the search of more subject specific error models to increase the
accuracy of joint kinematics estimations.