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  4. Error performances of a model-based biplane fluoroscopic system for tracking knee prosthesis during treadmill gait task
 
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research article

Error performances of a model-based biplane fluoroscopic system for tracking knee prosthesis during treadmill gait task

Barré, Arnaud
•
Aminian, Kamiar  
2018
Medical & biological engineering & computing

Roentgen stereophotogrammetry analysis technique allows an accurate measurement of knee joint prosthesis position and orientation using two X-ray images. Although this technique is used generally during static procedure, it is possible to use it with a biplane fluoroscopic system to measure the prosthesis kinematics during functional tasks (e.g., gait, squat, jump) performed in a laboratory environment. However, the performance of the system in terms of errors for the measurements and the model-based matching algorithm are not well known for dynamic tasks such as walking. The goal of this study was to estimate the static and dynamic errors of a model-based biplane fluoroscopic system for a treadmill gait task and analyze the error performance according to the speed and location of the knee joint prosthesis relative to X-ray sources. The results show a static maximum error (RMSE) of 0.13° for orientation and 0.06 mm for position for prosthesis components. The dynamic errors were different for each axis of the acquisition system and each prosthesis component. The largest dynamic error was along the vertical axis for the position (RMSE = 2.42 mm) and along the medio-lateral axis (perpendicular to movement) for the orientation (RMSE = 0.95°). As expected, the error depends on the distance between the prosthesis and the source in the acquisition system as well as the linear and angular velocity of the movement. The most accurate dynamic measure was around the centroid of the acquisition system, while kinematics measurements close to the X-rays detectors gave the worst errors.

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Type
research article
DOI
10.1007/s11517-017-1680-4
Author(s)
Barré, Arnaud
•
Aminian, Kamiar  
Date Issued

2018

Published in
Medical & biological engineering & computing
Volume

56

Start page

307

End page

316

Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LMAM  
FunderGrant Number

FNS

205320-137940

Available on Infoscience
September 3, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/139958
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