Abstract : Automatic classification of electrocardiogram (ECG) signals is vital for clinical diagnosis of hear
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Abstract : Automatic classification of electrocardiogram (ECG) signals is vital for clinical diagnosis of heart disease. This paper investigates the design of an efficient system for recognition of the premature ventricular contraction from the normal beats and other heart diseases. This system includes three main modules denoising module feature extraction module and classifier module. In the denoising module it is proposed the stationary wavelet transform for noise reduction of the electrocardiogram signals. In the feature extraction module a proper combination of the morphological-based features and timing interval-based features are proposed. As the classifier several supervised classifiers are investigated they are a number of multi-layer perceptron neural networks with different number of layers and training algorithms support vector machines with different kernel types radial basis function and probabilistic neural networks. Also for comparison the proposed features we have considered the wavelet-based features. It has done comprehensive simulations in order to achieve a high efficient system for ECG beat classification from 12 files obtained from the MIT-BIH arrhythmia database. Simulation results show that best results are achieved about 97.14 for classification of ECG beats.2010 Elsevier Ireland Ltd. All rights reserved.PMID 20510478 PubMed - indexed for MEDLINEMeSH TermsMeSH TermsArrhythmias Cardiac/diagnosisDatabases FactualElectrocardiography/classificationElectrocardiography/methods*Neural Networks (Computer)Signal Processing Computer-Assisted*LinkOut - more resourcesFull Text SourcesElsevier ScienceEBSCOOhioLINK Electronic Journal CenterSwets Information Services Supplemental Content Related citations High Efficient System for Automatic Classification of the Electrocardiogram Beats. Ann Biomed Eng. 2010 High Efficient System for Automatic Classification of the Electrocardiogram Beats.Zadeh AE Khazaee A. Ann Biomed Eng. 2010 Dec 8 . Epub 2010 Dec 8. Combined wavelet transformation and radial basis neural networks for classifying life-threatening cardiac arrhythmias. Med Biol Eng Comput. 1999 Combined wavelet transformation and radial basis neural networks for classifying life-threatening cardiac arrhythmias.al-Fahoum AS Howitt I. Med Biol Eng Comput. 1999 Sep 37(5)566-73. Classification of electrocardiogram signals with support vector machines and particle swarm optimization. IEEE Trans Inf Technol Biomed. 2008 Classification of electrocardiogram signals with support vector machines and particle swarm optimization.Melgani F Bazi Y. IEEE Trans Inf Technol Biomed. 2008 Sep 12(5)667-77. ECG beat classification by a novel hybrid neural network. Comput Methods Programs Biomed. 2001 ECG beat classification by a novel hybrid neural network.Dokur Z Olmez T. Comput Methods Programs Biomed. 2001 Sep 66(2-3)167-81. Review Noise and baseline wandering suppression of ECG signals by morphological filter. J Med Eng Technol. 2010 Review Noise and baseline wandering suppression of ECG signals by morphological filter.Taouli SA Bereksi-Reguig F. J Med Eng Technol. 2010 34(2)87-96. See reviews... See all... Recent activity Clear Turn Off Turn On Classification of the electrocardiogram signals using supervised classifiers and... Classification of the electrocardiogram signals using supervised classifiers and efficient features.Comput Methods Programs Biomed. 2010 Aug 99(2)179-94. Epub 2010 May 26 . PubMed Your browsing activity is empty. Activity recording is turned off. Turn recording back on See more... You are here NCBI gt Literature gt PubMed Write to the Help Desk Simple NCBI Directory Getting Started NCBI Education NCBI Help Manual NCBI Handbook Training amp Tutorials Resources Chemicals amp BioassaysData amp SoftwareDNA amp RNADomains amp StructuresGenes amp ExpressionGenetics amp MedicineGenomes amp MapsHomologyLiteratureProteinsSequence AnalysisTaxonomyTraining amp TutorialsVariation Popular PubMed Nucleotide BLAST PubMed Central Gene Bookshelf Protein OMIM Genome SNP Structure Featured GenBank Reference Sequences Map Viewer Genome Projects Human Genome Mouse Genome Influenza Virus Primer-BLAST Sequence Read Archive NCBI Information About NCBI Research at NCBI NCBI Newsletter NCBI FTP Site NCBI on Facebook NCBI on Twitter NCBI on YouTube NIH DHHS USA.gov Copyright | Disclaimer | Privacy | Accessibility | Contact National Center for Biotechnology Information U.S. National Library of Medicine 8600 Rockville Pike Bethesda MD 20894 USA
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