Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/12936
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%.
URI: http://bura.brunel.ac.uk/handle/2438/12936
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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