Cover Image

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 evaluate the stress distribution and fixation stability of the stem within t...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohd. Yusof, Baharuddin, Shaikh Salleh, Sheikh Hussain, Hamedi, Mahyar, Zulkifly, Ahmad Hafiz, Lee, Muhammad Hisyam, Mohd. Noor, Alias, A. Harris, Arief Ruhullah, Abdul Majid, Norazman
Format: Article
Published: Hindawi Publishing Corporation 2014
Subjects:
QH Natural history
Online Access:http://eprints.utm.my/id/eprint/62330/
http://dx.doi.org/10.1155/2014/478248
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.62330
record_format eprints
spelling my.utm.623302017-06-05T03:31:03Z http://eprints.utm.my/id/eprint/62330/ Primary stability recognition of the newly designed cementless femoral stem using digital signal processing Mohd. Yusof, Baharuddin Shaikh Salleh, Sheikh Hussain Hamedi, Mahyar Zulkifly, Ahmad Hafiz Lee, Muhammad Hisyam Mohd. Noor, Alias A. Harris, Arief Ruhullah Abdul Majid, Norazman QH Natural history 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 evaluate 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 transducer 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. Hindawi Publishing Corporation 2014 Article PeerReviewed Mohd. Yusof, Baharuddin and Shaikh Salleh, Sheikh Hussain and Hamedi, Mahyar and Zulkifly, Ahmad Hafiz and Lee, Muhammad Hisyam and Mohd. Noor, Alias and A. Harris, Arief Ruhullah and Abdul Majid, Norazman (2014) Primary stability recognition of the newly designed cementless femoral stem using digital signal processing. Biomed Research International, 2014 . ISSN 2314-6133 http://dx.doi.org/10.1155/2014/478248 DOI:10.1155/2014/478248
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QH Natural history
spellingShingle QH Natural history
Mohd. Yusof, Baharuddin
Shaikh Salleh, Sheikh Hussain
Hamedi, Mahyar
Zulkifly, Ahmad Hafiz
Lee, Muhammad Hisyam
Mohd. Noor, Alias
A. Harris, Arief Ruhullah
Abdul Majid, Norazman
Primary stability recognition of the newly designed cementless femoral stem using digital signal processing
description 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 evaluate 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 transducer 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.
format Article
author Mohd. Yusof, Baharuddin
Shaikh Salleh, Sheikh Hussain
Hamedi, Mahyar
Zulkifly, Ahmad Hafiz
Lee, Muhammad Hisyam
Mohd. Noor, Alias
A. Harris, Arief Ruhullah
Abdul Majid, Norazman
author_facet Mohd. Yusof, Baharuddin
Shaikh Salleh, Sheikh Hussain
Hamedi, Mahyar
Zulkifly, Ahmad Hafiz
Lee, Muhammad Hisyam
Mohd. Noor, Alias
A. Harris, Arief Ruhullah
Abdul Majid, Norazman
author_sort Mohd. Yusof, Baharuddin
title Primary stability recognition of the newly designed cementless femoral stem using digital signal processing
title_short Primary stability recognition of the newly designed cementless femoral stem using digital signal processing
title_full Primary stability recognition of the newly designed cementless femoral stem using digital signal processing
title_fullStr Primary stability recognition of the newly designed cementless femoral stem using digital signal processing
title_full_unstemmed Primary stability recognition of the newly designed cementless femoral stem using digital signal processing
title_sort primary stability recognition of the newly designed cementless femoral stem using digital signal processing
publisher Hindawi Publishing Corporation
publishDate 2014
url http://eprints.utm.my/id/eprint/62330/
http://dx.doi.org/10.1155/2014/478248
_version_ 1643655385381339136
score 13.211869

Similar Items