Subject-specific finite element modelling of the human foot
complex during walking : sensitivity analysis of material
properties, boundary and loading conditions

Akrami, M; Qian, Z; Zou, Z; Howard, D; Nester, CJ; Ren, L

Abstract

The objective of this study was to develop and validate
a subject-specific framework for modelling the human
foot. This was achieved by integrating medical image-based
finite element modelling, individualised multi-body musculoskeletal
modelling and 3D gait measurements. A 3D
ankle–foot finite element model comprising all major foot
structures was constructed based on MRI of one individual.
A multi-body musculoskeletal model and 3D gait measurements
for the same subject were used to define loading and
boundary conditions. Sensitivity analyses were used to investigate
the effects of key modelling parameters on model
predictions. Prediction errors of average and peak plantar
pressures were below 10% in all ten plantar regions at five
key gait events with only one exception (lateral heel, in early
stance, error of 14.44%). The sensitivity analyses results suggest
that predictions of peak plantar pressures are moderately
sensitive to material properties, ground reaction forces and
muscle forces, and significantly sensitive to foot orientation.
The maximum region-specific percentage change ratios
(peak stress percentage change over parameter percentage
change) were 1.935–2.258 for ground reaction forces, 1.528–
2.727 for plantar flexor muscles and 4.84–11.37 for foot
orientations. This strongly suggests that loading and boundary conditions need to be very carefully defined based on
personalised measurement data.

Citation

properties, boundary and loading conditions. Biomechanics and Modeling in Mechanobiology, 17(2), 559-576. https://doi.org/10.1007/s10237-017-0978-3

• Journal Article Type: Article
• Acceptance Date: Oct 31, 2017
• Online Publication Date: Nov 14, 2017
• Publication Date: Apr 1, 2018
• Deposit Date: Dec 12, 2017
• Publicly Available Date: Dec 12, 2017
• Journal: Biomechanics and Modeling in Mechanobiology
• Print ISSN: 1617-7959
• Electronic ISSN: 1617-7940
• Publisher: Springer Verlag
• Volume: 17
• Issue: 2
• Pages: 559-576
• DOI: https://doi.org/10.1007/s10237-017-0978-3
• Publisher URL: http://dx.doi.org/10.1007/s10237-017-0978-3
• Related Public URLs: https://link.springer.com/journal/10237