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A Hybrid Model of Maximum Margin Clustering Method and Support Vector Regression for Noninvasive Electrocardiographic Imaging
Joint Authors
Zhang, Huaxiong
Liu, Feng
Shou, Guofa
Wang, Yaming
Huang, Wenqing
Jiang, Mingfeng
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-11-01
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Noninvasive electrocardiographic imaging, such as the reconstruction of myocardial transmembrane potentials (TMPs) distribution, can provide more detailed and complicated electrophysiological information than the body surface potentials (BSPs).
However, the noninvasive reconstruction of the TMPs from BSPs is a typical inverse problem.
In this study, this inverse ECG problem is treated as a regression problem with multi-inputs (BSPs) and multioutputs (TMPs), which will be solved by the Maximum Margin Clustering- (MMC-) Support Vector Regression (SVR) method.
First, the MMC approach is adopted to cluster the training samples (a series of time instant BSPs), and the individual SVR model for each cluster is then constructed.
For each testing sample, we find its matched cluster and then use the corresponding SVR model to reconstruct the TMPs.
Using testing samples, it is found that the reconstructed TMPs results with the MMC-SVR method are more accurate than those of the single SVR method.
In addition to the improved accuracy in solving the inverse ECG problem, the MMC-SVR method divides the training samples into clusters of small sample sizes, which can enhance the computation efficiency of training the SVR model.
American Psychological Association (APA)
Jiang, Mingfeng& Liu, Feng& Wang, Yaming& Shou, Guofa& Huang, Wenqing& Zhang, Huaxiong. 2012. A Hybrid Model of Maximum Margin Clustering Method and Support Vector Regression for Noninvasive Electrocardiographic Imaging. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-9.
https://search.emarefa.net/detail/BIM-472125
Modern Language Association (MLA)
Jiang, Mingfeng…[et al.]. A Hybrid Model of Maximum Margin Clustering Method and Support Vector Regression for Noninvasive Electrocardiographic Imaging. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-9.
https://search.emarefa.net/detail/BIM-472125
American Medical Association (AMA)
Jiang, Mingfeng& Liu, Feng& Wang, Yaming& Shou, Guofa& Huang, Wenqing& Zhang, Huaxiong. A Hybrid Model of Maximum Margin Clustering Method and Support Vector Regression for Noninvasive Electrocardiographic Imaging. Computational and Mathematical Methods in Medicine. 2012. Vol. 2012, no. 2012, pp.1-9.
https://search.emarefa.net/detail/BIM-472125
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-472125