NDLI: A multiple-classifier architecture for ECG beat classification

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A multiple-classifier architecture for ECG beat classification

Content Provider	IEEE Xplore Digital Library
Author	Palreddy, S. Yu Hen Hu Mani, V. Tompkins, W.J.
Copyright Year	1997
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA (Palreddy, S.)
Abstract	We investigate the use of the modular architecture of multiple clustering based pattern classifiers for ECG beat classification using the MIT/BIH arrhythmia database. The feature space is divided into several regions and individual classifiers are developed for each region separately. Then the outputs of these classifiers are combined using two competing combination rules: a winner decides all method and a distance-based combination method. Experiment results indicated that multiple classifier approach yields better sensitivity and classification rate.
Starting Page	172
Ending Page	181
File Size	576906
Page Count	10
File Format	PDF
ISBN	0780342569
ISSN	10893555
DOI	10.1109/NNSP.1997.622396
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-09-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrocardiography Computer architecture Pattern classification Training data Spatial databases Morphology Shape Heart beat Heart rate variability Self organizing feature maps
Content Type	Text
Resource Type	Article

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