Document Detail


Application of higher order cumulants to ECG signals for the cardiac health diagnosis.
MedLine Citation:
PMID:  22254652     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Electrocardiogram (ECG) is the P-QRS-T wave which indicates the electrical activity of the heart. The subtle changes in the amplitude and duration of the ECG signal depict the cardiac abnormality. It is very difficult to decipher these minute changes by the naked eye. Hence, a computer-aided diagnosis system will help the physicians to monitor the cardiac health. The ECG is a nonlinear and non-stationary signal. Hence, the hidden information in the ECG signal can be extracted using nonlinear method. In this paper, we have automatically classified normal and abnormal beats using higher order spectra (HOS) cumulants of wavelet packet decomposition (WPD). The abnormal beats are ventricular premature contractions (VPC) and Atrial premature contractions (APC). These HOS cumulant features of the WPD are subjected to principal component analysis (PCA) to reduce the number of features to five. Finally these features were fed to the support vector machine (SVM) with kernel functions for automatic classification. In our work, we have obtained the highest accuracy of 98.4% sensitivity and specificity of 98.9% and 98.0% respectively with radial basis function (RBF) kernel function and Meyer's wavelet (dmey) function. Our system is ready clinically to run on large amount of data sets.
Authors:
Roshan J Martis; U Rajendra Acharya; Ajoy K Ray; Chandan Chakraborty
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  2011     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2011  
Date Detail:
Created Date:  2012-01-18     Completed Date:  2012-06-12     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1697-700     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Cardiac Complexes, Premature / diagnosis*
Diagnosis, Computer-Assisted / methods*
Electrocardiography / methods*
Humans
Nonlinear Dynamics
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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