Detecting atrial fibrillation from short single lead ECGs using statistical and morphological features

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dc.contributor.authorAthif, M
dc.contributor.authorYasawardene, PC
dc.contributor.authorDaluwatte, C
dc.date.accessioned2023-04-19T09:28:30Z
dc.date.available2023-04-19T09:28:30Z
dc.date.issued2018
dc.description.abstractObjective: Point of care ECG devices can improve the early detection of atrial fibrillation (AF). The efficiency of such devices depends on the capability of automatic AF detection against normal sinus rhythm and other arrhythmias from a short single lead ECG record in the presence of noise and artifacts. The objective of this study was to develop an algorithm that classifies a short single lead ECG record into 'Normal', 'AF', 'Other' and 'Noisy' classes, and identify the challenges in developing such algorithms and potential mitigation steps.en_US
dc.identifier.citationAthif, M., Yasawardene, P. C., & Daluwatte, C. (2018). Detecting atrial fibrillation from short single lead ECGs using statistical and morphological features. Physiological Measurement, 39(6), 064002. https://doi.org/10.1088/1361-6579/aac552en_US
dc.identifier.databaseNational Library of Medicineen_US
dc.identifier.doi10.1088/1361-6579/aac552.en_US
dc.identifier.issn1361-6579en_US
dc.identifier.journalPhysiological Measurementen_US
dc.identifier.pgnos064002en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/20886
dc.identifier.volume39en_US
dc.identifier.year2018en_US
dc.language.isoen_USen_US
dc.subjectNatural fractured bituminous coalen_US
dc.subjectCoal matrix swellingen_US
dc.subjectSuper-critical CO2en_US
dc.subjectN2 saturationen_US
dc.subjectPermeability recoveryen_US
dc.titleDetecting atrial fibrillation from short single lead ECGs using statistical and morphological featuresen_US
dc.typeArticle-Full-texten_US

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