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A model presented for classification ECG signals base on Case-Based Reasoning

Journal of Soft Computing and Applications. 2013;2013:1-9 DOI 10.5899/2013/jsca-00020


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Journal Title: Journal of Soft Computing and Applications

ISSN: 2195-576X (Online)

Publisher: International Scientific Publications and Consulting Services (ISPACS)

LCC Subject Category: Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software

Country of publisher: Germany

Language of fulltext: English

Full-text formats available: PDF



Elaheh Sayari

Mahdi Yaghoobi


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Time From Submission to Publication: 12 weeks


Abstract | Full Text

Early detection of heart diseases/abnormalities can prolong life and enhance the quality of living through appropriate treatment; thus classifying cardiac signals will be helped to immediate diagnosing of heart beat type in cardiac patients. The present paper utilizes the case base reasoning (CBR) for classification of ECG signals. Four types of ECG beats (normal beat, congestive heart failure beat, ventricular tachyarrhythmia beat and atrial fibrillation beat) obtained from the PhysioBank database was classified by the proposed CBR model. The main purpose of this article is classifying heart signals and diagnosing the type of heart beat in cardiac patients that in proposed CBR (Case Base Reasoning) system, Training and testing data for diagnosing and classifying types of heart beat have been used. The evaluation results from the model are shown that the proposed model has high accuracy in classifying heart signals and helps to clinical decisions for diagnosing the type of heart beat in cardiac patients which indeed has high impact on diagnosing the type of heart beat aided computer.