Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/113991
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dc.contributor.author | Elgendi, M. | - |
dc.contributor.author | Meo, M. | - |
dc.contributor.author | Abbott, D. | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Bioengineering, 2016; 3(4):26-1-26-14 | - |
dc.identifier.issn | 2306-5354 | - |
dc.identifier.issn | 2306-5354 | - |
dc.identifier.uri | http://hdl.handle.net/2440/113991 | - |
dc.description.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. | - |
dc.description.statementofresponsibility | Mohamed Elgendi, Marianna Meo and Derek Abbott | - |
dc.language.iso | en | - |
dc.publisher | Multidisciplinary Digital Publishing Institute | - |
dc.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/). | - |
dc.source.uri | http://dx.doi.org/10.3390/bioengineering3040026 | - |
dc.subject | Mobile health; affordable healthcare; numerically-efficient algorithms | - |
dc.title | A proof-of-concept study: simple and effective detection of P and T waves in arrhythmic ECQ signals | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.3390/bioengineering3040026 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Abbott, D. [0000-0002-0945-2674] | - |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
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hdl_113991.pdf | Published version | 1.92 MB | Adobe PDF | View/Open |
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