Bournemouth University Research Online [BURO] - Monitoring the suitability of the fit of a lower-limb prosthetic socket using artificial neural network in commonly encountered walking conditions.
Skip to main content Login Bournemouth University Home About Browse Repository statistics Monitoring the suitability of the fit of a lower-limb prosthetic socket using artificial neural network in commonly encountered walking conditions. Tools Tools Tools RDF+XML BibTeX RIOXX2 XML RDF+N-Triples JSON RefWorks Dublin Core FP7 Dublin Core Atom Simple Metadata Refer METS HTML Citation ASCII Citation OpenURL ContextObject EndNote OpenURL ContextObject in Span MODS MPEG-21 DIDL EP3 XML Reference Manager RDF+N3 Multiline CSV Davenport, P., Noroozi, S., Sewell, P. and Zahedi, S., 2017. Monitoring the suitability of the fit of a lower-limb prosthetic socket using artificial neural network in commonly encountered walking conditions. In: First World Congress on Condition Monitoring 2017 (WCCM 2017), 13-16 June 2017, ILEC Conference Centre, London, UK. Full text available as: Preview PDF WCCM Paper.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. 11MB Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. Abstract Prosthetic sockets are still routinely designed without the aid of quantitative measurement, relying instead on the experience and skill of clinicians. Sockets remain the most common cause for complaint regarding the suitability of a prosthesis, and poor pressure distribution is implicated in many forms of unacceptable care outcomes. Monitoring pressure distribution has been effectively restricted to laboratory settings, and only limited work has examined conditions other than flat walking. In this work, a transtibial amputee completed static and dynamic tasks on flat ground, on slopes and with changes to prosthetic materials and alignment. This was achieved using a set of wireless measurement nodes and custom LabView and MATLAB code, using external strain measurements and a neural network to understand the internal pressure distribution. Future work will focus on modifying the software to be more user-friendly for a clinical operator, and in simplifying the required hardware. Although the system in its current form facilitated the desired measurements effectively, it required engineering support to function accurately. Improving the reliability and stability of the system will be necessary before routine use is possible. Item Type: Conference or Workshop Item (Paper) Group: Faculty of Science & Technology ID Code: 29823 Deposited By: Unnamed user with email symplectic@symplectic Deposited On: 04 Oct 2017 08:25 Last Modified: 15 Aug 2021 09:22 Downloads Downloads per month over past year More statistics for this item... Repository Staff Only - © Bournemouth University 2006 - 2019. All rights reserved. Charitable status Website privacy & cookies Copyright and terms of use Research Library Access to Information
