DocumentCode :
2315769
Title :
Fuzzy clustering neural network for classification of ECG beats
Author :
Osowski, S. ; Linh, Tran Hoai
Author_Institution :
Inst. of the Theory of Electr. Eng. & Electr. Meas., Warsaw Univ. of Technol., Poland
Volume :
5
fYear :
2000
fDate :
2000
Firstpage :
26
Abstract :
The paper presents the application of fuzzy self-organizing neural network and higher order statistics for ECG beat classification. The new classification algorithm of the ECG beats, applying the higher order statistics and fuzzy self-organizing neural classifier has been proposed in the paper. The cumulants of the second, third and fourth orders have been used for the feature selection. The GK algorithm for self-organization of the neural network has been applied. The results of experiments have confirmed good efficiency of the proposed solution. The investigations show that the method may find practical application in the recognition of beats. The main features of the proposed method are the good efficiency and real time performance
Keywords :
electrocardiography; fuzzy neural nets; medical signal processing; pattern classification; pattern clustering; self-organising feature maps; ECG beat classification; ECG beats; feature selection; fuzzy self-organizing neural classifier; fuzzy self-organizing neural network; self-organization; Classification algorithms; Clustering algorithms; Electrocardiography; Fuzzy neural networks; Higher order statistics; Morphology; Neural networks; Paper technology; Partitioning algorithms; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
ISSN :
1098-7576
Print_ISBN :
0-7695-0619-4
Type :
conf
DOI :
10.1109/IJCNN.2000.861430
Filename :
861430
Link To Document :
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