DocumentCode
1748932
Title
A novel approach for assessing interfacial pressure between the prosthetic socket and the residual limb for below knee amputees using artificial neural networks
Author
Amali, R. ; Noroozi, S. ; Vinney, J. ; Sewell, P. ; Andrews, S.
Author_Institution
Fac. of Eng., Univ. of the West of England, Bristol, UK
Volume
4
fYear
2001
fDate
2001
Firstpage
2689
Abstract
So far the study of interfacial pressures between residual limb and the prosthetic socket has not led to the design of any useful tool that can assist the prosthetist to fit a prosthesis. Researchers at the UWE Bristol have found a novel methodology that can revolutionise this process. It is based on the combined application of a hybrid numerical method and experimental finite element analysis for stress analysis. This paper represents part of the development process of this tool and discusses the step forward from a two-dimensional analysis, discussed previously (2000), into a 3D symmetrical shell analysis which is intended to simulate a structured and ideal socket. The authors feel this is a logical step, which is necessary for understanding the relationship between surface stress/strain, and internal load, which causes those surface stresses. This paper emphasises the significance of this statement because it requires no knowledge of tissue properties
Keywords
backpropagation; feedforward neural nets; finite element analysis; medical computing; neural nets; prosthetics; stress analysis; backpropagation; finite element analysis; interfacial pressure; knee amputees; multilayer neural networks; prosthetic socket; residual limb; surface stress analysis; Artificial neural networks; Backpropagation; Finite element methods; Internal stresses; Neural networks; Neural prosthesis; Neurons; Prosthetics; Sockets; Transducers;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-7044-9
Type
conf
DOI
10.1109/IJCNN.2001.938795
Filename
938795
Link To Document