ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

the “joint” constraints configuration from Speirs et al.
[12]. Node constraints were selected at the femoral
head, the fossa intercondylaris and epicondyle
lateralis (Figure 1). All points were constrained in the
local coordinate system (LCS). The bone intensity
values were converted into material properties
(0.05GPa < E < 17GPa, Poisson ratio = 0.3) [13, 14]
and mapped onto each node of the FE mesh which
consisted of 129’600 C3D10 elements and 191532
nodes. For the calculations, the commercial software
package ABAQUS was used. Mises stress and
magnitude of displacement for all nodes were
collected from all simulations.
Figure 1: Setup of the FE model for normal walking
situation - (F1) Hip contact force at point P0; (F2)
Abductor group at point P1; (F3) Tensor fascia latae,
proximal part at point P1; (F4) Tensor fascia latae,
distal part at point P1; (F5) Vastus lateralis at point
P2. Orientation of the coordinate system of the femur
(GCS) and the adapted local coordinate system
(LCS) for the boundary conditions.
3.3 Predictive model
The extracted stresses and displacements were used to build their respective database of
numerical results by using single value decomposition. Nonlinear iterative partial least
squares (NIPALS) regression was used to establish a relationship between the model
input parameters (geometry, mechanical properties and loading) and the numerical FE
predictions. For the predictions, a representation of 98% was used for both stress and
displacement models, where the displacement model showed higher compactness than
the Mises stress prediction model. Finally, the accuracy of the models predictions was
evaluated on 25 bone samples (Figure 2).
4. RESULTS
For a first prediction, which included femoral head displacement and maximum Mises
stress in three regions, the response of the bones could be predicted by an average
relative accuracy between 1.1% and 16%, with a negligible calculation time (a few
milliseconds). The accuracy increases drastically by including the loading scenario in
the predictive model as well as when more components are used in the PLS regression
(Figure 3). Secondly, the prediction of the full response of Mises stress and
displacement magnitude for all 25 was carried out (Figure 4). The average absolute
prediction error for the Mises stresses was 0.01 +/- 0.46 MPa and for the displacement
magnitude 0.001 +/- 0.05 mm.