Title :
A neural network approach for bone fracture healing assessment
Author :
Kaufman, J.J. ; Chiabrera, A. ; Hatem, M. ; Hakim, N.Z. ; Figueiredo, M. ; Nasser, P. ; Lattuga, S. ; Pilla, A.A. ; Siffert, R.S.
Author_Institution :
Dept. of Orthopedics, Mount Sinai Sch. of Med., New York, NY, USA
Abstract :
An approach based on auscultatory percussion, a technique used by some orthopedists both for bone fracture detection and bone fracture healing assessment, is described. Low-frequency, low-intensity mechanical power, very much like the finger tap of orthopedists, is used to evaluate the vibrational response of the bone. The novel element is the data processing, which incorporates specialized preprocessing and a neural network for estimating fractured bone strength. In addition, a new mathematical model for the vibrational response of a fractured limb, which provides data to design and test the neural network processing scheme, is presented. An experimental procedure is described for acquiring real data from animal and human fractures in a form necessary for neural network input.<>
Keywords :
biomechanics; bone; fracture; medical diagnostic computing; neural nets; physiological models; animal fractures; auscultatory percussion; bone fracture detection; bone fracture healing assessment; data processing; fractured bone strength; fractured limb; human fractures; low frequency low intensity mechanical power; mathematical model; neural network approach; neural network input; neural network processing scheme; specialized preprocessing; vibrational response; Bones; Fingers; Injuries; Joints; Mathematical model; Mechanical factors; Neural networks; Orthopedic surgery; Radiography; Vibrations;
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
