Medical Engineering & Physics
Volume 28, Issue 8 , Pages 809-815, October 2006

Cardiac state diagnosis using adaptive neuro-fuzzy technique☆

  • N. Kannathal

      Affiliations

    • ECE Division, NgeeAnn Polytechnic, 535, Clementi Road, Singapore 599489, Singapore
    • Department of Electrical and Computer Engineering Division, National University of Singapore, Singapore
    • Corresponding Author InformationCorresponding author. Tel.: +65 64606482.
    • ,
  • C.M. Lim

      Affiliations

    • ECE Division, NgeeAnn Polytechnic, 535, Clementi Road, Singapore 599489, Singapore
    • ,
  • U. Rajendra Acharya

      Affiliations

    • ECE Division, NgeeAnn Polytechnic, 535, Clementi Road, Singapore 599489, Singapore
    • ,
  • P.K. Sadasivan

      Affiliations

    • Department of Electrical and Computer Engineering Division, National University of Singapore, Singapore

Received 8 December 2004; received in revised form 22 November 2005; accepted 25 November 2005. published online 23 January 2006.

Abstract 

Analysis of heart rate has become a popular noninvasive tool for assessing the activities of the autonomic nervous system (ANS). These signals may either contain indicators of a current disease or even warnings about impending diseases. However, to manually study and pinpoint heart abnormalities in voluminous data is strenuous and time consuming. Here, an adaptive neuro-fuzzy network is used to classify heart abnormalities in 10 different cardiac states and shown to be effective. The results indicate a high level of efficacy of tools used with an accuracy level of more than 94%.

Keywords: Electrocardiogram, Neuro-fuzzy, Heart rate, Spectral entropy, Poincare plot

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☆ A complete complex of an ECG, starting with the P-wave, followed by the QRS-complex and the T-wave

PII: S1350-4533(05)00253-5

doi:10.1016/j.medengphy.2005.11.011

Medical Engineering & Physics
Volume 28, Issue 8 , Pages 809-815, October 2006

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