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Technical Briefs

Comparative Assessment of Bone Pose Estimation Using Point Cluster Technique and OpenSim

[+] Author and Article Information
Rebecca L. Lathrop

Department of Mechanical and Aerospace Engineering,  The Ohio State University, Columbus, OH 43210

Ajit M. W. Chaudhari

Department of Mechanical and Aerospace Engineering,  The Ohio State University, Columbus, OH 43210; Department of Orthopaedics, The Ohio State University, Columbus, OH 43210

Robert A. Siston1

Department of Mechanical and Aerospace Engineering,  The Ohio State University, Columbus, OH 43210; Department of Orthopaedics, The Ohio State University, Columbus, OH 43210

1

Corresponding Author: Robert A. Siston, Department of Mechanical and Aerospace Engineering, E305 Scott Laboratory, 201 W. 19th Avenue, Columbus, OH 43210, USA, e-mail: siston.1@osu.edu

J Biomech Eng 133(11), 114503 (Nov 28, 2011) (6 pages) doi:10.1115/1.4005409 History: Received August 04, 2011; Revised October 28, 2011; Posted October 31, 2011; Published November 28, 2011; Online November 28, 2011

Estimating the position of the bones from optical motion capture data is a challenge associated with human movement analysis. Bone pose estimation techniques such as the Point Cluster Technique (PCT) and simulations of movement through software packages such as OpenSim are used to minimize soft tissue artifact and estimate skeletal position; however, using different methods for analysis may produce differing kinematic results which could lead to differences in clinical interpretation such as a misclassification of normal or pathological gait. This study evaluated the differences present in knee joint kinematics as a result of calculating joint angles using various techniques. We calculated knee joint kinematics from experimental gait data using the standard PCT, the least squares approach in OpenSim applied to experimental marker data, and the least squares approach in OpenSim applied to the results of the PCT algorithm. Maximum and resultant RMS differences in knee angles were calculated between all techniques. We observed differences in flexion/extension, varus/valgus, and internal/external rotation angles between all approaches. The largest differences were between the PCT results and all results calculated using OpenSim. The RMS differences averaged nearly 5° for flexion/extension angles with maximum differences exceeding 15°. Average RMS differences were relatively small (< 1.08°) between results calculated within OpenSim, suggesting that the choice of marker weighting is not critical to the results of the least squares inverse kinematics calculations. The largest difference between techniques appeared to be a constant offset between the PCT and all OpenSim results, which may be due to differences in the definition of anatomical reference frames, scaling of musculoskeletal models, and/or placement of virtual markers within OpenSim. Different methods for data analysis can produce largely different kinematic results, which could lead to the misclassification of normal or pathological gait. Improved techniques to allow non-uniform scaling of generic models to more accurately reflect subject-specific bone geometries and anatomical reference frames may reduce differences between bone pose estimation techniques and allow for comparison across gait analysis platforms.

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Copyright © 2011 by American Society of Mechanical Engineers
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Figures

Grahic Jump Location
Figure 5

Despite meticulous manual adjustment, experimental and virtual markers may not lie directly on top of one another in the static pose. Additionally, scaling generic models to represent individual subjects is often inaccurate. For example, although the femur can be scaled to allow the experimentally placed femoral epicondylar markers to lie on the bone, the greater trochanter markers may not be in contact with the model. These slight virtual marker placement mismatches could produce differences in knee kinematics between techniques.

Grahic Jump Location
Figure 4

Femoral bone geometry can vary between subjects including differences in the frontal plane such as proximal tapering (a.1) or bowing (a.2). The generic bone model of the femur in OpenSim (b) can be orthogonally scaled and rotated, but may not account for all subject-specific parameters and can result in an angular offset between the lab-calculated and OpenSim approximated reference frames, seen in (c.1) and (c.2) as the angle α in the frontal plane.

Grahic Jump Location
Figure 3

(a) Flexion/Extension, (b) Varus/Valgus, and (c) Internal/External angles from a representative subject. Very little difference was seen when only weighting within OpenSim was changed. The largest difference was seen between PCT results and all other results. The curves generally appear to have slight differences in shape, and are offset by a constant amount throughout the gait cycle. (d) Manual removal of the constant offset between waveforms by subtracting the average value of each curve from the PCT results demonstrates that the internal/external rotation angle waveforms are similar in shape, and that differences were largely driven by the constant offset.

Grahic Jump Location
Figure 2

Anatomical reference frames for the right leg were defined as follows: for the femur (a), a temporary X-axis was defined from lateral to medial epicondyle, the Z-axis from functional hip joint center to the midpoint between the lateral and medial epicondyles, the Y-axis as the cross product of the Z-axis and temporary X-axis, and the orthogonal X was then defined from the cross product of Y and Z. For the tibia (b), a temporary X-axis was defined from the lateral to medial tibial plateau, the Z-axis from the midpoint between the tibial plateaus to the midpoint of a line connecting the lateral and medial malleoli, and the Y-axis as the cross product of the Z-axis and the temporary X-axis. Again, the orthogonal X-axis was defined from the cross product of Y and Z.

Grahic Jump Location
Figure 1

(a) Markers were placed on the skin following the Point Cluster Technique placement convention. (b) Virtual markers were affixed to the musculoskeletal models of the lower extremities in OpenSim using the entire PCT placement convention or (c) from the 4 virtual markers representing the segment reference frame as calculated by the PCT algorithm.

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