Bone fracture healing assessment using a neural network

Author

Kaufman, J.J. ; Chiabrera, A. ; Hakim, N. ; Hatem, M. ; Figueiredo, M. ; Nasser, P. ; Lattuga, S. ; Trent, P. ; Pilla, A.A. ; Siffert, R.S.

fYear

1990

fDate

17-21 June 1990

Firstpage

53

Abstract

A method is proposed to estimate the strength of a healing fractured bone. A four-port electrical network model of the low-frequency (50 Hz-1 kHz) transverse vibration response of a healing fractured bone is derived using Timoshenko beam theory. A back-propagation neural net with one hidden layer processes computer simulated bone fracture model data, and classifies it with respect to the fracture gap stiffness, relative to intact bone. The effect on classification accuracy of the number of hidden units and preprocessing of the data is evaluated. Vibration measurements from a rabbit fracture model and clinical patient data are also presented

Keywords

biology computing; biomechanics; bone; classification; fracture; medical computing; neural nets; vibrations; 50 to 1000 Hz; Timoshenko beam theory; back-propagation neural net; bone fracture healing assessment; bone strength estimation; classification accuracy; clinical patient data; computer simulation; four-port electrical network model; fracture gap stiffness; hidden layer; preprocessing; rabbit; transverse vibration response;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1990., 1990 IJCNN International Joint Conference on

Conference_Location

San Diego, CA, USA

Type

conf

DOI

10.1109/IJCNN.1990.137694

Filename

5726653