A Metaheuristic Optimization Approach for Parameter Estimation in Arrhythmia Classification from Unbalanced Data

A Metaheuristic Optimization Approach for Parameter Estimation in Arrhythmia Classification from Unbalanced Data

The electrocardiogram records the heart’s electrical activity and generates a significant amount of data. The analysis of these data helps us to detect diseases and disorders via heart bio-signal abnormality classification. In unbalanced-data contexts, where the classes are not equally represented,...

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Bibliographic Details
Main Authors: Juan Carlos Carrillo-Alarcón, Luis Alberto Morales-Rosales, Héctor Rodríguez-Rángel, Mariana Lobato-Báez, Antonio Muñoz, Ignacio Algredo-Badillo
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Sensors
Subjects:
electrocardiogram (ECG)
signal processing
machine learning
arrhythmia
unbalanced
Online Access:https://www.mdpi.com/1424-8220/20/11/3139

Internet

https://www.mdpi.com/1424-8220/20/11/3139

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