Output details
15 - General Engineering
Bournemouth University
Improvements in the accuracy of an Inverse Problem Engine's output for the prediction of below-knee prosthetic socket interfacial loads
This research was shortlisted for a Times Higher Education Award 2010 in the category of “Outstanding Engineering Research Team of the Year”. It reports on a novel method for improving the output of neural networks and its effectiveness demonstrated through a case study involving the assessmement of the load distribution in a prosthetic socket. The results presented in this paper have underpinned a successful EPSRC CASE Award application with the UK’s largest prosthetic technology company, Chas A Blatchford & Sons Ltd (£80K) (Grant Ref: EP/H501045/1; http://fastuk.org/research/projview.php?id=1707) which aims to put a smart prosthetic socket into production.