Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.medengphy.2005.11.011
Title: Cardiac state diagnosis using adaptive neuro-fuzzy technique
Authors: Kannathal, N.
Lim, C.M.
Rajendra Acharya, U.
Sadasivan, P.K. 
Keywords: Electrocardiogram
Heart rate
Neuro-fuzzy
Poincare plot
Spectral entropy
Issue Date: Oct-2006
Source: Kannathal, N., Lim, C.M., Rajendra Acharya, U., Sadasivan, P.K. (2006-10). Cardiac state diagnosis using adaptive neuro-fuzzy technique. Medical Engineering and Physics 28 (8) : 809-815. ScholarBank@NUS Repository. https://doi.org/10.1016/j.medengphy.2005.11.011
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%. © 2005 IPEM.
Source Title: Medical Engineering and Physics
URI: http://scholarbank.nus.edu.sg/handle/10635/55255
ISSN: 13504533
DOI: 10.1016/j.medengphy.2005.11.011
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