A Proof-of-Concept Study: Simple and Effective Detection of P and T Waves in Arrhythmic ECG Signals

UBC Faculty Research and Publications

A Proof-of-Concept Study: Simple and Effective Detection of P and T Waves in Arrhythmic ECG Signals Elgendi, Mohamed; Meo, Marianna; Abbott, Derek

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.

Item Metadata

Title	A Proof-of-Concept Study: Simple and Effective Detection of P and T Waves in Arrhythmic ECG Signals
Creator	Elgendi, Mohamed; Meo, Marianna; Abbott, Derek
Contributor	Children's Hospital (Vancouver, B.C.)
Publisher	Multidisciplinary Digital Publishing Institute
Date Issued	2016-10-17
Description	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.
Subject	Mobile health; Affordable healthcare; Numerically-efficient algorithms
Genre	Article
Type	Text
Language	eng
Date Available	2019-05-28
Provider	Vancouver : University of British Columbia Library
Rights	CC BY 4.0
DOI	10.14288/1.0379040
URI	http://hdl.handle.net/2429/70361
Affiliation	Medicine, Faculty of; Other UBC; Non UBC; Obstetrics and Gynaecology, Department of
Citation	Bioengineering 3 (4): 26 (2016)
Publisher DOI	10.3390/bioengineering3040026
Peer Review Status	Reviewed
Scholarly Level	Faculty
Rights URI	https://creativecommons.org/licenses/by/4.0/
Aggregated Source Repository	DSpace

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