Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/12936
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dc.contributor.authorAbbod, M-
dc.contributor.authorShieh, JS-
dc.coverage.spatialTaipei, Taiwan-
dc.date.accessioned2016-07-14T10:47:37Z-
dc.date.available2016-07-14T10:47:37Z-
dc.date.issued2016-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/12936-
dc.description.abstractAtrial 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%.en_US
dc.language.isoenen_US
dc.sourceThe 8th International High Speed Intelligent Communication Forum & 2016 International Conference On Communication Problem-Solving-
dc.sourceThe 8th International High Speed Intelligent Communication Forum & 2016 International Conference On Communication Problem-Solving-
dc.titlePredicting the Percentage of Atrial Fibrillation using Sample Entropyen_US
dc.typeConference Paperen_US
pubs.finish-date2016-09-09-
pubs.finish-date2016-09-09-
pubs.publication-statusSubmitted-
pubs.start-date2016-09-07-
pubs.start-date2016-09-07-
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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