Recognition of heartbeats using support vector machine networks: a comparative study

Authors:
Stanisław Osowski;Tran Haoi Linh;Tomasz Markiewicz
Affiliations:
Warsaw University of Technology and Military University of Technology, Warsaw, Poland;Hanoi University of Technology, Hanoi, Vietnam;Warsaw University of Technology
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

Citing 2
Cited 0

Combining Pattern Classifiers: Methods and Algorithms

Combining Pattern Classifiers: Methods and Algorithms
A comparison of methods for multiclass support vector machines

IEEE Transactions on Neural Networks

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Abstract

The paper presents the comparison of performance of the individual and ensemble of SVM classifiers for the recognition of abnormal heartbeats on the basis of the registered ECG waveforms. The recognition system applies two different Support Vector Machine based classifiers and the ensemble systems composed of the individual classifiers combined together in different way to obtain the best possible performance on the ECG data. The results of numerical experiments using the data of MIT BIH Arrhythmia Database have confirmed the superior performance of the proposed solution.