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DC Field | Value | Language |
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dc.contributor.author | Abbod, M | - |
dc.contributor.author | Shieh, JS | - |
dc.coverage.spatial | Taipei, Taiwan | - |
dc.date.accessioned | 2016-07-14T10:47:37Z | - |
dc.date.available | 2016-07-14T10:47:37Z | - |
dc.date.issued | 2016 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/12936 | - |
dc.description.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%. | en_US |
dc.language.iso | en | en_US |
dc.source | The 8th International High Speed Intelligent Communication Forum & 2016 International Conference On Communication Problem-Solving | - |
dc.source | The 8th International High Speed Intelligent Communication Forum & 2016 International Conference On Communication Problem-Solving | - |
dc.title | Predicting the Percentage of Atrial Fibrillation using Sample Entropy | en_US |
dc.type | Conference Paper | en_US |
pubs.finish-date | 2016-09-09 | - |
pubs.finish-date | 2016-09-09 | - |
pubs.publication-status | Submitted | - |
pubs.start-date | 2016-09-07 | - |
pubs.start-date | 2016-09-07 | - |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
Files in This Item:
File | Description | Size | Format | |
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Fulltext.doc | 270.5 kB | Microsoft Word | View/Open |
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