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Discrimination of cardiac arrhythmias using a fuzzy rule-based method

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2 Author(s)
Chowdhury, E. ; New Mexico State Univ., Las Cruces, NM, USA ; Ludeman, L.C.

The authors propose a relatively simple but robust fuzzy rule-based method to accurately distinguish between normal sinus rhythm (NSR), malignant ventricular fibrillation (VF) and ventricular tachycardia (VT). The method first subjectively identifies the "qualitative" features of pre-processed electrocardiogram (ECG) signals necessary to discriminate between NSR, VF and VT. Second, the parameters of fuzzy sets, namely the real-valued membership functions for "small", "medium" and "large", are defined so that qualitative features are quantitatively interpreted. Finally, a set of fuzzy "if-then" rules is constructed to discriminate between NSR, VF and VT which uses the defined membership functions. This technique was applied to portions of the MIT/BIH Malignant Ventricular Arrhythmia Database and results show correct classification for 94.3% of NSR, 82% of VT and 78% of VF events.<>

Published in:

Computers in Cardiology 1994

Date of Conference:

25-28 Sept. 1994

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