Using computed tomography (CT) or magnetic resonance (MR) images to construct 3D knee models has been widely used in biomedical engineering research. Statistical shape modeling (SSM) method is an alternative way to provide a fast, cost-efficient, and subject-specific knee modeling technique. This study was aimed to evaluate the feasibility of using a combined dual-fluoroscopic imaging system (DFIS) and SSM method to investigate in vivo knee kinematics. Three subjects were studied during a treadmill walking. The data were compared with the kinematics obtained using a CT-based modeling technique. Geometric root-mean-square (RMS) errors between the knee models constructed using the SSM and CT-based modeling techniques were 1.16 mm and 1.40 mm for the femur and tibia, respectively. For the kinematics of the knee during the treadmill gait, the SSM model can predict the knee kinematics with RMS errors within 3.3 deg for rotation and within 2.4 mm for translation throughout the stance phase of the gait cycle compared with those obtained using the CT-based knee models. The data indicated that the combined DFIS and SSM technique could be used for quick evaluation of knee joint kinematics.
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December 2014
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Prediction of In Vivo Knee Joint Kinematics Using a Combined Dual Fluoroscopy Imaging and Statistical Shape Modeling Technique
Jing-Sheng Li,
Jing-Sheng Li
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
College of Health and Rehabilitation
Sciences: Sargent College,
Sciences: Sargent College,
Boston University
,Boston, MA 02215
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Tsung-Yuan Tsai,
Tsung-Yuan Tsai
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
Search for other works by this author on:
Shaobai Wang,
Shaobai Wang
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
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Pingyue Li,
Pingyue Li
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
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Young-Min Kwon,
Young-Min Kwon
Department of Orthopaedic Surgery,
and Harvard Medical School,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
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Andrew Freiberg,
Andrew Freiberg
Department of Orthopaedic Surgery,
and Harvard Medical School,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
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Harry E. Rubash,
Harry E. Rubash
Department of Orthopaedic Surgery,
and Harvard Medical School,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
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Guoan Li
Guoan Li
1
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
e-mail: gli1@mgh.harvard.edu
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
e-mail: gli1@mgh.harvard.edu
1Corresponding author.
Search for other works by this author on:
Jing-Sheng Li
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
College of Health and Rehabilitation
Sciences: Sargent College,
Sciences: Sargent College,
Boston University
,Boston, MA 02215
Tsung-Yuan Tsai
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
Shaobai Wang
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
Pingyue Li
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
Young-Min Kwon
Department of Orthopaedic Surgery,
and Harvard Medical School,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
Andrew Freiberg
Department of Orthopaedic Surgery,
and Harvard Medical School,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
Harry E. Rubash
Department of Orthopaedic Surgery,
and Harvard Medical School,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
Guoan Li
Bioengineering Laboratory,
Department of Orthopaedic Surgery,
and Harvard Medical School,
e-mail: gli1@mgh.harvard.edu
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
e-mail: gli1@mgh.harvard.edu
1Corresponding author.
Manuscript received February 13, 2014; final manuscript received September 16, 2014; accepted manuscript posted October 16, 2014; published online October 30, 2014. Assoc. Editor: Kenneth Fischer.
J Biomech Eng. Dec 2014, 136(12): 124503 (6 pages)
Published Online: October 30, 2014
Article history
Received:
February 13, 2014
Revision Received:
September 16, 2014
Accepted:
October 16, 2014
Citation
Li, J., Tsai, T., Wang, S., Li, P., Kwon, Y., Freiberg, A., Rubash, H. E., and Li, G. (October 30, 2014). "Prediction of In Vivo Knee Joint Kinematics Using a Combined Dual Fluoroscopy Imaging and Statistical Shape Modeling Technique." ASME. J Biomech Eng. December 2014; 136(12): 124503. https://doi.org/10.1115/1.4028819
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