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An artificial intelligence approach for measurement and monitoring of pressure at the residual limb/socket interface - A clinical study

Amali, Ramin; Noroozi, Siamak; Vinney, John; Sewell, Philip; Andrews, Stephen

Authors

Dr Ramin Amali Ramin2.Amali@uwe.ac.uk
Dean and Head of School of Engineering

Siamak Noroozi

John Vinney

Philip Sewell

Stephen Andrews



Abstract

A good-fitting prosthetic socket requires the pressure between the stump and socket to be distributed to ensure the load is carried by pressure tolerant regions of the limb. Transducers and Finite Element Analysis have been utilised to measure and monitor these pressures. However, it has been recognised that both techniques have limitations, making them impractical for everyday clinical use to aid the prosthetist in the socket fitting process. This paper details the design of a Hybrid Inverse Problem Engine (HIPE) which combines Artificial Intelligence (AI) and experimental/numerical data to create a less invasive and passive approach to develop a practical clinical tool for predicting the pressure distribution at the limb/socket interface. Testing and validation of the HIPE under laboratory conditions showed that the technique was able to predict the location and magnitude of pressures applied manually to the socket. A comparison of the predicted pressure distribution found using the HIPE, at the limb/socket interface of a patient in a clinical environment with photoelastic data of the actual pressure distribution, further indicated the technique's potential benefits. It is hoped that the HIPE will eventually become a general tool suitable for monitoring the fit of a prosthesis in a clinical environment.

Citation

Amali, R., Noroozi, S., Vinney, J., Sewell, P., & Andrews, S. (2008). An artificial intelligence approach for measurement and monitoring of pressure at the residual limb/socket interface - A clinical study. Insight - Non-Destructive Testing & Condition Monitoring, 50(7), 374-383. https://doi.org/10.1784/insi.2008.50.7.374

Journal Article Type Article
Publication Date Jul 1, 2008
Deposit Date Dec 11, 2012
Journal Insight: Non-Destructive Testing and Condition Monitoring
Print ISSN 1354-2575
Publisher British Institute of Non-destructive Testing
Peer Reviewed Not Peer Reviewed
Volume 50
Issue 7
Pages 374-383
DOI https://doi.org/10.1784/insi.2008.50.7.374
Keywords artificial intelligence, residual limb/socket interface pressure, ann, prosthetics, hybrid inverse problem engine
Public URL https://uwe-repository.worktribe.com/output/1010875
Publisher URL http://dx.doi.org/10.1784/insi.2008.50.7.374