Surface-marker cluster design criteria for 3-D bone movement reconstruction

Abstract

When three-dimensional (3-D) human or animal movement is recorded using a photogrammetric system, bone-embedded frame positions and orientations are estimated from reconstructed surface marker trajectories using either nonoptimal or optimal algorithms. The effectiveness of these mathematical procedures in accommodating for both photogrammetric errors and skin movement artifacts depends on the number of markers associated with a given bone as well as on the size and shape characteristics of the relevant cluster. One objective of this paper deals with the identification of marker-cluster design criteria aimed at the minimization of error propagation from marker coordinates to bone-embedded frame position and orientation. Findings allow for the quantitative estimation of these errors for any given cluster configuration and suggest the following main design criteria. A cluster made up of four markers represents a good practical compromise. Planar clusters are acceptable, provided in quasi-isotropic distribution. The root mean square distance of the markers from their centroid should be greater than ten times the standard deviation of the marker position error. The second objective of this paper deals with the identification of the optimal cluster position and orientation on the limb aimed at the minimization of error propagation to anatomical landmark laboratory coordinates. Cluster position should be selected to minimize skin movement artifacts. The longest principal axis of the marker distribution should be oriented toward the relevant anatomical landmark position.

Precision of shoulder anatomical landmark calibration by two approaches: A CAST-like protocol and a new anatomical palpator method

“…Another disadvantage, like other methods based on marker cluster to track segment trajectories, is the shape of the cluster and soft tissue artifacts [8,9]. Artifact minimization can be obtained, similar to this study, using cluster configuration including four markers [13,11,23] to permit further data optimization [24].…”

“…Unfortunately, the fiducial landmarks are set on the skin surface of the individual undergoing the motion analysis. In such configuration, the discrepancy between the respective location of the tracked RMs and the corresponding ALs is depending on soft tissue displacement and thickness of the analyzed segment, leading to skin artifacts [11]. The CAST protocol has been created to try to minimize the above discrepancy using the tip of a calibrated stick set as close as possible to the AL-of-interest.…”

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait

“…The cluster of M skin-markers on the thigh was characterized by a group of N TCPEs based on all combinations of three markers, excluding those having a 2D isotropy index smaller than 0.5, which has been shown to cause large orientation errors (Cappozzo et al, 1997). For each TCPE, the marker cluster configuration during the static trial was used as the reference configuration.…”

“…Moreover, the rigid component has been demonstrated to be the only one impacting pose estimation accuracy when using RBLS Dumas et al, 2015;Grimpampi et al, 2014). This explains why commonly used BPEs based on RBLS, which compensate only for the non-rigid component (Cappozzo et al, 1997;Grimpampi et al, 2014;Heller et al, 2011;Söderkvist and Wedin, 1993;Veldpaus et al, 1988), are insufficient to fully compensate for the STA effects (Cereatti et al, 2006;Stagni and Fantozzi, 2009).…”

Bone Pose Estimation in the Presence of Soft Tissue Artifact Using Triangular Cosserat Point Elements

“…Moreover, the average rotational parameter (11) and the average translational parameter J T of the J th TCPE relative to all other TCPEs at time t is defined as:…”