Document Detail

Classification of cardiac abnormalities using heart rate signals.
MedLine Citation:
PMID:  15191072     Owner:  NLM     Status:  MEDLINE    
The heart rate is a non-stationary signal, and its variation can contain indicators of current disease or warnings about impending cardiac diseases. The indicators can be present at all times or can occur at random, during certain intervals of the day. However, to study and pinpoint abnormalities in large quantities of data collected over several hours is strenuous and time consuming. Hence, heart rate variation measurement (instantaneous heart rate against time) has become a popular, non-invasive tool for assessing the autonomic nervous system. Computer-based analytical tools for the in-depth study and classification of data over day-long intervals can be very useful in diagnostics. The paper deals with the classification of cardiac rhythms using an artificial neural network and fuzzy relationships. The results indicate a high level of efficacy of the tools used, with an accuracy level of 80-85%.
R Acharya; A Kumar; P S Bhat; C M Lim; S S Iyengar; N Kannathal; S M Krishnan
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Medical & biological engineering & computing     Volume:  42     ISSN:  0140-0118     ISO Abbreviation:  Med Biol Eng Comput     Publication Date:  2004 May 
Date Detail:
Created Date:  2004-06-11     Completed Date:  2004-08-30     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  7704869     Medline TA:  Med Biol Eng Comput     Country:  England    
Other Details:
Languages:  eng     Pagination:  288-93     Citation Subset:  IM    
Department of ECE, Ngee Ann Polytechnic, Singapore.
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MeSH Terms
Arrhythmias, Cardiac / classification,  diagnosis*
Diagnosis, Differential
Electrocardiography, Ambulatory
Fuzzy Logic
Neural Networks (Computer)
Signal Processing, Computer-Assisted*

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