Knee Joint Vibration Signal Analysis with Matching Pursuit Decomposition and Dynamic Weighted Classifier Fusion
Joint Authors
Cai, Suxian
Krishnan, Sridhar
Zheng, Fang
Lu, Meng
Yang, Shanshan
Wu, Yunfeng
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-03-12
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Analysis of knee joint vibration (VAG) signals can provide quantitative indices for detection of knee joint pathology at an early stage.
In addition to the statistical features developed in the related previous studies, we extracted two separable features, that is, the number of atoms derived from the wavelet matching pursuit decomposition and the number of significant signal turns detected with the fixed threshold in the time domain.
To perform a better classification over the data set of 89 VAG signals, we applied a novel classifier fusion system based on the dynamic weighted fusion (DWF) method to ameliorate the classification performance.
For comparison, a single leastsquares support vector machine (LS-SVM) and the Bagging ensemble were used for the classification task as well.
The results in terms of overall accuracy in percentage and area under the receiver operating characteristic curve obtained with the DWF-based classifier fusion method reached 88.76% and 0.9515, respectively, which demonstrated the effectiveness and superiority of the DWF method with two distinct features for the VAG signal analysis.
American Psychological Association (APA)
Cai, Suxian& Yang, Shanshan& Zheng, Fang& Lu, Meng& Wu, Yunfeng& Krishnan, Sridhar. 2013. Knee Joint Vibration Signal Analysis with Matching Pursuit Decomposition and Dynamic Weighted Classifier Fusion. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-506810
Modern Language Association (MLA)
Cai, Suxian…[et al.]. Knee Joint Vibration Signal Analysis with Matching Pursuit Decomposition and Dynamic Weighted Classifier Fusion. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-11.
https://search.emarefa.net/detail/BIM-506810
American Medical Association (AMA)
Cai, Suxian& Yang, Shanshan& Zheng, Fang& Lu, Meng& Wu, Yunfeng& Krishnan, Sridhar. Knee Joint Vibration Signal Analysis with Matching Pursuit Decomposition and Dynamic Weighted Classifier Fusion. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-506810
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-506810