Morgan Eveleigh – Abstract

A finite element method for integrated design and testing of 3D printed ankle and foot orthoses for children with cerebral palsy and motor impairment

Eveleigh M[1], Howlin P[2], Stebbins J[3], Kilic K[4], Reid R[4] and Brodie M[1,5]
1. Graduate School of Biomedical Engineering, University of NSW, Sydney, Australia
2. School of Mechanical and Manufacturing Engineering, University of NSW, Sydney, Australia
3. Oxford Gait Laboratory, Nuffield Orthopaedic Centre, Oxford, United Kingdom
4. AbilityMate, Sydney, Australia
5. NeuRA, Sydney, Australia

Cerebral palsy (CP) affects approximately two in every thousand babies born in developed countries and causes debilitating gait impairments, [1-4] which may be remedied with ankle and foot orthoses (AFOs). Current methods of manufacturing AFOs are expensive and time-consuming; 3d-printing may provide an efficient and cost-effective alternative. A systematic review [5] was conducted and revealed that computer simulations of AFOs are under-utilised for design optimisation and pre-manufacture testing.

The hypothesis tested was that a novel integrated design and testing approach, incorporating finite element (FE) modelling could be used to predict the strength, stiffness and buckling of paediatric AFOs. Topology optimisation was used to produce three new designs with reduced (85%, 66% and 38%) mass. The three models were 3d-printed and the predicted AFO performance validated against results from a mechanical testing rig.

The FE model predicted the buckling of the new designs and also changes in stiffness and strength with normalised errors ranging from 0.7% to 16%. Both predicted and actual AFO strength decreased significantly (p<0.05) with reduced mass (24.8 Nm for 100% to 2.14 Nm for 38%). Strength loss could be minimised through more complex designs.

This novel method may be used to predict and optimise orthoses properties during the design stage. With further research it may be possible to precisely match the mass and design of a 3d-printed AFO to a child’s mass and gait pattern. The use of simulation-based methods to efficiently produce optimised designs may assist children with CP and motor impairment to walk better.

  1. Bertens, L.C., et al., Development and validation of a model to predict the risk of exacerbations in chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis, 2013. 8: p. 493-9