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Publications in Scientific Journals:

A. Synek, D. H. Pahr:
"Plausibility and Parameter Sensitivity of Micro-Finite Element-Based Joint Load Prediction at the Proximal Femur";
Biomechanics and Modeling in Mechanobiology, 17 (2018), 3; 843 - 852.



English abstract:
A micro-finite element-based method to estimate the bone loading history based on bone architecture was recently presented in the literature. However, a thorough investigation of the parameter sensitivity and plausibility of this method to predict joint loads is still missing. The goals of this study were (1) to analyse the parameter sensitivity of the joint load predictions at one proximal femur and (2) to assess the plausibility of the results by comparing load predictions of ten proximal femora to in vivo hip joint forces measured with instrumented prostheses (available from www.orthoload.com). Joint loads were predicted by optimally scaling the magnitude of four unit loads (inclined −20∘
to 100∘ with respect to the vertical axis) applied to micro-finite element models created from high-resolution computed tomography scans (30.3 μm voxel size). Parameter sensitivity analysis was performed by varying a total of nine parameters and showed that predictions of the peak load directions (range 10∘-30∘) are more robust than the predicted peak load magnitudes (range 2344.8-4689.5 N). Comparing the results of all ten femora with the in vivo loading data of ten subjects showed that peak loads are plausible both in terms of the load direction (in vivo: 18.2±2.0∘, predicted: 20.0∘) and magnitude (in vivo: 2707.6±443.3 N, predicted: 3372.2±597.9 N). Overall, this study suggests that micro-finite element-based joint load predictions are both plausible and robust in terms of the predicted peak load direction, but predicted load magnitudes should be interpreted with caution.


"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1007/s10237-017-0996-1


Created from the Publication Database of the Vienna University of Technology.