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BioMed Research International
Volume 2014 (2014), Article ID 478248, 9 pages
Research Article

Primary Stability Recognition of the Newly Designed Cementless Femoral Stem Using Digital Signal Processing

1Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603 Lembah Pantai, Kuala Lumpur, Malaysia
2Centre for Biomedical Engineering Transportation Research Alliance, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
3Department of Orthopaedic, Traumatology & Rehabilitation, Kuliyyah of Medicine, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia
4Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

Received 15 November 2013; Revised 20 February 2014; Accepted 6 March 2014; Published 1 April 2014

Academic Editor: Yoshinobu Sato

Copyright © 2014 Mohd Yusof Baharuddin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.