Application of Entropy-Based Features to Predict Defibrillation Outcome in Cardiac Arrest

Application of Entropy-Based Features to Predict Defibrillation Outcome in Cardiac Arrest

Prediction of defibrillation success is of vital importance to guide therapy and improve the survival of patients suffering out-of-hospital cardiac arrest (OHCA). Currently, the most efficient methods to predict shock success are based on the analysis of the electrocardiogram (ECG) during ventricula...

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Bibliographic Details
Main Authors: Beatriz Chicote, Unai Irusta, Raúl Alcaraz, José Joaquín Rieta, Elisabete Aramendi, Iraia Isasi, Daniel Alonso, Karlos Ibarguren
Format: Article
Language:English
Published: MDPI AG 2016-08-01
Series:Entropy
Subjects:
ventricular fibrillation
defibrillation
shock outcome prediction
out-of-hospital cardiac arrest
non-linear dynamics
entropy measures
regularity-based entropies
predictability-based entropies
fuzzy entropy
Online Access:http://www.mdpi.com/1099-4300/18/9/313

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