Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/113991
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Type: Journal article
Title: A proof-of-concept study: simple and effective detection of P and T waves in arrhythmic ECQ signals
Author: Elgendi, M.
Meo, M.
Abbott, D.
Citation: Bioengineering, 2016; 3(4):26-1-26-14
Publisher: Multidisciplinary Digital Publishing Institute
Issue Date: 2016
ISSN: 2306-5354
2306-5354
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Responsibility: 
Mohamed Elgendi, Marianna Meo and Derek Abbott
Abstract: A robust and numerically-efficient method based on two moving average filters, followed by a dynamic event-related threshold, has been developed to detect P and T waves in electrocardiogram (ECG) signals as a proof-of-concept. Detection of P and T waves is affected by the quality and abnormalities in ECG recordings; the proposed method can detect P and T waves simultaneously through a unique algorithm despite these challenges. The algorithm was tested on arrhythmic ECG signals extracted from the MIT-BIH arrhythmia database with 21,702 beats. These signals typically suffer from: (1) non-stationary effects; (2) low signal-to-noise ratio; (3) premature atrial complexes; (4) premature ventricular complexes; (5) left bundle branch blocks; and (6) right bundle branch blocks. Interestingly, our algorithm obtained a sensitivity of 98.05% and a positive predictivity of 97.11% for P waves, and a sensitivity of 99.86% and a positive predictivity of 99.65% for T waves. These results, combined with the simplicity of the method, demonstrate that an efficient and simple algorithm can suit portable, wearable, and battery-operated ECG devices.
Keywords: Mobile health; affordable healthcare; numerically-efficient algorithms
Rights: © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
DOI: 10.3390/bioengineering3040026
Published version: http://dx.doi.org/10.3390/bioengineering3040026
Appears in Collections:Aurora harvest 8
Computer Science publications

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