DocumentCode
2490422
Title
Knowledge-based approach in the classification of beat waveforms
Author
Taddei, A. ; Gagliano, R. ; Marchesi, C.
Author_Institution
CNR Inst. of Clinical Physiol., Pisa, Italy
fYear
1991
fDate
23-26 Sep 1991
Firstpage
609
Lastpage
612
Abstract
The authors describe a method for the classification of the beat morphology in long-term electrocardiograms (ECGs). Each QRS-T complex is represented in terms of elementary waveforms extracted from the ECG signal. These waveforms constitute the set of symbols associated with each beat and the related geometrical parameters are their attributes. A knowledge-based system was developed using the Nexpert Object tool for a membership mapping of the ECG beats. Annotated ECG databases (VALE, MIT-BIH) were used for evaluating the classification system
Keywords
electrocardiography; knowledge based systems; medical diagnostic computing; MIT-BIH; Nexpert Object tool; QRS-T complex; VALE; annotated ECG databases; beat morphology classification; beat waveforms; elementary waveforms; geometrical parameters; knowledge-based system; long-term electrocardiograms; symbols set; Biomedical monitoring; Cardiac disease; Computerized monitoring; Electrocardiography; Morphology; Pathology; Pattern recognition; Physiology; Signal analysis; Spatial databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Computers in Cardiology 1991, Proceedings.
Conference_Location
Venice
Print_ISBN
0-8186-2485-X
Type
conf
DOI
10.1109/CIC.1991.168985
Filename
168985
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