Document Detail


Probabilistic finite element predictions of the human lower limb model in total knee replacement.
MedLine Citation:
PMID:  23317551     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
The purpose of this paper is to explore both an extended and a reduced set of input parameters of the Finite Element (FE) model of the human lower limb with a Total Knee Replacement (TKR) implant. The most influential parameters in determining the size and the shape of the performance envelopes of eight kinematics and peak contact pressure output variables of the tibio-femoral joint and the patello-femoral joint are sought. The lower limb FE model, which includes bones, TKR implant, soft tissues and applied forces of realistic size, is used in the context of the stair ascent simulation. Two probabilistic methods are used together with the FE model to generate the performance envelopes and to explore the sensitivities of the input parameters of the FE model: the Monte Carlo simulation and the Response Surface Method (RSM). A total of four probabilistic FE analyses assess how the uncertainties in an extended set of 77 input variables and a reduced set of 22 input variables obtained from the RSM/sensitivity analyses affect the performance envelopes. It is shown that the FE model with the reduced set of variables is able to replicate the full FE model. The differences between the Monte Carlo envelopes of performance obtained with the FE model with the full set of variables and the FE model with the reduced set of variables were on average over all output measures under 1.67mm for translations, 1.75° for rotations and under 2MPa for peak contact pressures. The differences between the RSM and the Monte Carlo envelopes of performances obtained with the reduced set of input variables were, on average, over all output measures under 0.75mm for translations, 1.26° for rotations and 2.39MPa for peak contact pressures. While saving computational time with the reduced set of variables, the findings are especially of high importance to the orthopedic surgeons who would like to know the most important parameters that can influence the performance of the TKR for a given human activity.
Authors:
C T C Arsene; B Gabrys
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-10
Journal Detail:
Title:  Medical engineering & physics     Volume:  -     ISSN:  1873-4030     ISO Abbreviation:  Med Eng Phys     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9422753     Medline TA:  Med Eng Phys     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.
Affiliation:
Bioengineering Science Research Group, School of Engineering Sciences, University of Southampton, Southampton, SO17 1BJ, UK. Electronic address: arsenecorneliu@yahoo.co.uk.
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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