Document Detail


Automatic classification of heartbeats using wavelet neural network.
MedLine Citation:
PMID:  20703646     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
The electrocardiogram (ECG) signal is widely employed as one of the most important tools in clinical practice in order to assess the cardiac status of patients. The classification of the ECG into different pathologic disease categories is a complex pattern recognition task. In this paper, we propose a method for ECG heartbeat pattern recognition using wavelet neural network (WNN). To achieve this objective, an algorithm for QRS detection is first implemented, then a WNN Classifier is developed. The experimental results obtained by testing the proposed approach on ECG data from the MIT-BIH arrhythmia database demonstrate the efficiency of such an approach when compared with other methods existing in the literature.
Authors:
Radhwane Benali; Fethi Bereksi Reguig; Zinedine Hadj Slimane
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Publication Detail:
Type:  Journal Article     Date:  2010-07-13
Journal Detail:
Title:  Journal of medical systems     Volume:  36     ISSN:  0148-5598     ISO Abbreviation:  J Med Syst     Publication Date:  2012 Apr 
Date Detail:
Created Date:  2012-03-27     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7806056     Medline TA:  J Med Syst     Country:  United States    
Other Details:
Languages:  eng     Pagination:  883-92     Citation Subset:  IM    
Affiliation:
Biomedical Engineering Laboratory, Department of Electronics, Faculty of Engineering Sciences, Abou Bekr Belkaid University, Tlemcen, Algeria, benali_redouane@yahoo.fr.
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