Athif, MYasawardene, PCDaluwatte, C2023-04-192023-04-192018Athif, 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/aac5521361-6579http://dl.lib.uom.lk/handle/123/20886Objective: 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-USNatural fractured bituminous coalCoal matrix swellingSuper-critical CO2N2 saturationPermeability recoveryArticle-Full-text2018Physiological Measurement39National Library of Medicine06400210.1088/1361-6579/aac552.