Verification of Manual Digitization Methods During Experimental Simulation of Knee MotionSource: Journal of Verification, Validation and Uncertainty Quantification:;2020:;volume( 005 ):;issue: 003::page 031004-1DOI: 10.1115/1.4048748Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Cadaveric testing is a common approach for verifying mathematical algorithms in computational modeling. In models of total knee replacement (TKR) motion, model inputs commonly include rigid body motions defined using the Grood–Suntay spatial linkage between tibial and femoral components. This approach requires definition of coordinate systems for each rigid TKR component based on fiducial points, manual digitization of a point cloud within the experimental setup, and registration of the orientation relative to bone marker arrays. This study compared variability between two different manual point digitization methods (hand-held stylus and pivot tool each registered in an optical tracking system). This was accomplished by verifying the mathematical algorithm used to calculate the coordinate system from digitized points and quantifying the variability of the digitization methods in a simulated cadaver limb experimental setup. For the hand-held stylus method, the standard deviation was 0.50 mm for the origin and 1.31, 0.51, and 0.62 deg for the x–y–z axes, respectively. Required digitization of each rigid marker array created additional errors of 0.54 mm for the origin and 1.70, 1.66, and 0.98 deg for the x–y–z axes, respectively. For the pivot tool method, the standard deviation was 0.35 mm for the origin and 0.37, 1.27, and 1.24 deg for the x–y–z axes, respectively. In this experimental setup, the pivot tool was the better option for minimizing error while providing repeatable manual digitization of fiducial points and point clouds.
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contributor author | Hargett, Zachary | |
contributor author | Gutierrez, Manuel | |
contributor author | Harman, Melinda | |
date accessioned | 2022-02-05T22:11:12Z | |
date available | 2022-02-05T22:11:12Z | |
date copyright | 10/29/2020 12:00:00 AM | |
date issued | 2020 | |
identifier issn | 2377-2158 | |
identifier other | vvuq_005_03_031004.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4277084 | |
description abstract | Cadaveric testing is a common approach for verifying mathematical algorithms in computational modeling. In models of total knee replacement (TKR) motion, model inputs commonly include rigid body motions defined using the Grood–Suntay spatial linkage between tibial and femoral components. This approach requires definition of coordinate systems for each rigid TKR component based on fiducial points, manual digitization of a point cloud within the experimental setup, and registration of the orientation relative to bone marker arrays. This study compared variability between two different manual point digitization methods (hand-held stylus and pivot tool each registered in an optical tracking system). This was accomplished by verifying the mathematical algorithm used to calculate the coordinate system from digitized points and quantifying the variability of the digitization methods in a simulated cadaver limb experimental setup. For the hand-held stylus method, the standard deviation was 0.50 mm for the origin and 1.31, 0.51, and 0.62 deg for the x–y–z axes, respectively. Required digitization of each rigid marker array created additional errors of 0.54 mm for the origin and 1.70, 1.66, and 0.98 deg for the x–y–z axes, respectively. For the pivot tool method, the standard deviation was 0.35 mm for the origin and 0.37, 1.27, and 1.24 deg for the x–y–z axes, respectively. In this experimental setup, the pivot tool was the better option for minimizing error while providing repeatable manual digitization of fiducial points and point clouds. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Verification of Manual Digitization Methods During Experimental Simulation of Knee Motion | |
type | Journal Paper | |
journal volume | 5 | |
journal issue | 3 | |
journal title | Journal of Verification, Validation and Uncertainty Quantification | |
identifier doi | 10.1115/1.4048748 | |
journal fristpage | 031004-1 | |
journal lastpage | 031004-5 | |
page | 5 | |
tree | Journal of Verification, Validation and Uncertainty Quantification:;2020:;volume( 005 ):;issue: 003 | |
contenttype | Fulltext |