Please use this identifier to cite or link to this item:
Title: Predicting the Percentage of Atrial Fibrillation using Sample Entropy
Authors: Abbod, M
Shieh, JS
Issue Date: 2016
Abstract: Atrial fibrillation is the most commonly confronted cardiac arrhythmia in humans. This paper is written to use sample entropy and percentage of atrial fibrillation as a measure of regularity to measure AF. To assume the percentage of AF, 25 long term ECG recordings of human subjects with atrial fibrillation containing a total of 299 AF episodes were processed. The mean and SD of percentage breaking point in all the subjects from the MIT-BIH Atrial Fibrillation database was 0.6057±0.0863, and its sample entropy is 0.3522±0.1509. The mean and SD for sample entropy at 100% AF is 1.0669±0.4521. This data is used to predict the percentage of AF at a given sample entropy value. Our study concludes that the early detection of AF can be initiated by the AF already happened for 60%.
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext.docFile is embargoed until 01/12/2017270.5 kBMicrosoft WordView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.