Heart arrhythmia diagnosis based on the combination of morphological, frequency and nonlinear features of ECG signals and metaheuristic feature selection algorithm

•A new method for discrimination of seven types of ECG beats is proposed.•This method employs a combination of morphology, frequency, and nonlinear indices.•Application of feature selection (include GA, PSO, DE, and NSGA-II) is discussed.•KNN, RBFNN, FF-net, Fit-net, and Pat-net are employed for cla...

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Bibliographic Details
Published in:	Expert systems with applications Vol. 161; p. 113697
Main Authors:	Mazaheri, Vajihe, Khodadadi, Hamed
Format:	Journal Article
Language:	English
Published:	New York Elsevier Ltd 15.12.2020 Elsevier BV
Subjects:	Abnormalities Arrhythmia Cardiac arrhythmia Cardiac arrhythmia recognition Classification Diagnosis ECG signal Electrocardiography Feature extraction FF net classifier Genetic algorithms Heart diseases Heuristic methods Machine learning Meta-heuristic optimization algorithm Morphology Multiple objective analysis Neural networks Nonlinear indices Optimization Optimization algorithms Pattern recognition Physicians Radial basis function Signal processing Sorting algorithms Meta-heuristic optimization algorithm Cardiac arrhythmia recognition ECG signal FF net classifier Nonlinear indices
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
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