Primary stability recognition of the newly designed cementless femoral stem using digital signal processing

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems.The correlation of experimental validation with finite element analysis (FEA) is commonly used to valuate the stress distribution and fixation stability of the stem within the...

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Bibliographic Details
Main Authors: Baharuddin, Mohd Yusof, Salleh, Sh-Hussain, Hamedi, Mahyar, Zulkifly, Ahmad Hafiz, Lee, Muhammad Hisyam, Mohd Noor, Alias, A. Harris, Arief Ruhullah, Abdul Majid, Norazman
Format: Article
Language:English
English
English
Published: Hindawi Publishing Corporation 2014
Subjects:
Online Access:http://irep.iium.edu.my/38251/
http://irep.iium.edu.my/38251/
http://irep.iium.edu.my/38251/
http://irep.iium.edu.my/38251/1/38251_Primary%20stability%20recognition.pdf
http://irep.iium.edu.my/38251/2/38251_Primary%20stability%20recognition_SCOPUS.pdf
http://irep.iium.edu.my/38251/3/38251_Primary%20stability%20recognition_WOS.pdf
Description
Summary:Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems.The correlation of experimental validation with finite element analysis (FEA) is commonly used to valuate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct ransducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes.The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion.This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.