  Reliability theory is used to assess the sensitivity of a passive flexion and
active flexion of the human lower leg Finite Element (FE) models with Total
Knee Replacement (TKR) to the variability in the input parameters of the
respective FE models. The sensitivity of the active flexion simulating the
stair ascent of the human lower leg FE model with TKR was presented before in
[1,2] whereas now in this paper a comparison is made with the passive flexion
of the human lower leg FE model with TKR. First, with the Monte Carlo
Simulation Technique (MCST), a number of randomly generated input data of the
FE model(s) are obtained based on the normal standard deviations of the
respective input parameters. Then a series of FE simulations are done and the
output kinematics and peak contact pressures are obtained for the respective FE
models (passive flexion and/or active flexion models). Seven output performance
measures are reported for the passive flexion model and one more parameter was
reported for the active flexion FE model (patello-femoral peak contact
pressure) in [1]. A sensitivity study will be performed based on the Response
Surface Method (RSM) to identify the key parameters that influence the
kinematics and peak contact pressures of the passive flexion FE model. Another
two MCST and RSM-based probabilistic FE analyses will be performed based on a
reduced list of 19 key input parameters. In total 4 probabilistic FE analyses
will be performed: 2 probabilistic FE analyses (MCST and RSM) based on an
extended set of 78 input variables and another 2 probabilistic FE analyses
(MCST and RSM) based on a reduced set of 19 input variables. Due to the likely
computation cost in order to make hundreds of FE simulations with MCST, a
high-performance and distributed computing system will be used for the passive
flexion FE model the same as it was used for the active flexion FE model in
[1].
