• 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