A Crucial Wave Detection and Delineation Method for Twelve-Lead ECG Signals

Delineating the crucial waves in electrocardiogram records is a paramount work for the automatic diagnosis system of heart diseases. In this paper, a novel method is described to determine the boundaries and the peaks of P waves, QRS complexes and T waves by utilizing twelve-lead electrocardiogram s...

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Autores principales:	Genlang Chen, Maolin Chen, Jiajian Zhang, Liang Zhang, Chaoyi Pang
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2020
Materias:	ECG twelve-lead signals local distance transform detection delineation Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/bce6402565e1471bb4774c54176e3720
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spelling	oai:doaj.org-article:bce6402565e1471bb4774c54176e37202021-11-19T00:04:27ZA Crucial Wave Detection and Delineation Method for Twelve-Lead ECG Signals2169-353610.1109/ACCESS.2020.2965334https://doaj.org/article/bce6402565e1471bb4774c54176e37202020-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/8954716/https://doaj.org/toc/2169-3536Delineating the crucial waves in electrocardiogram records is a paramount work for the automatic diagnosis system of heart diseases. In this paper, a novel method is described to determine the boundaries and the peaks of P waves, QRS complexes and T waves by utilizing twelve-lead electrocardiogram signals. It avoids the difficulty of setting the thresholds when determining the boundaries of crucial waves and also the trouble of selection of wavelet basis as the wavelet-based method does. The signals are first preprocessed by a bandpass filter. After that, the locations of QRS complexes are identified. And based on the QRS locations, adaptive search windows are set to detect the locations of P waves and T waves. Then, a method called local distance transform decides the wave boundary in each lead. Finally, the final boundary determination rule is applied to obtain reliable boundaries. We justify the performance of our algorithm on LUDB database. When the tolerance window interval is 40ms, the peak accuracies of P wave, QRS complex and T wave are all beyond 98% and their boundary accuracies are all above 96%. Compared with the derivative threshold method and the wavelet-based method where the tolerance window interval is 150ms, the algorithm shows a sensitivity and a positive predictive value of peaks and boundaries greater than or equal to 98.43% and 96.44% for the P wave, 99.89% and 99.86% for the QRS complex and 99.21% and 99.85% for the T wave. For the critera of average error and standard deviation, our method has the performance similar to those methods. In addition, our algorithm can also handle such several situations where the boundary determination of crucial waves is tough as high T wave, high noise and baseline wandering well.Genlang ChenMaolin ChenJiajian ZhangLiang ZhangChaoyi PangIEEEarticleECGtwelve-lead signalslocal distance transformdetectiondelineationElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 8, Pp 10707-10717 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	ECG twelve-lead signals local distance transform detection delineation Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	ECG twelve-lead signals local distance transform detection delineation Electrical engineering. Electronics. Nuclear engineering TK1-9971 Genlang Chen Maolin Chen Jiajian Zhang Liang Zhang Chaoyi Pang A Crucial Wave Detection and Delineation Method for Twelve-Lead ECG Signals
description	Delineating the crucial waves in electrocardiogram records is a paramount work for the automatic diagnosis system of heart diseases. In this paper, a novel method is described to determine the boundaries and the peaks of P waves, QRS complexes and T waves by utilizing twelve-lead electrocardiogram signals. It avoids the difficulty of setting the thresholds when determining the boundaries of crucial waves and also the trouble of selection of wavelet basis as the wavelet-based method does. The signals are first preprocessed by a bandpass filter. After that, the locations of QRS complexes are identified. And based on the QRS locations, adaptive search windows are set to detect the locations of P waves and T waves. Then, a method called local distance transform decides the wave boundary in each lead. Finally, the final boundary determination rule is applied to obtain reliable boundaries. We justify the performance of our algorithm on LUDB database. When the tolerance window interval is 40ms, the peak accuracies of P wave, QRS complex and T wave are all beyond 98% and their boundary accuracies are all above 96%. Compared with the derivative threshold method and the wavelet-based method where the tolerance window interval is 150ms, the algorithm shows a sensitivity and a positive predictive value of peaks and boundaries greater than or equal to 98.43% and 96.44% for the P wave, 99.89% and 99.86% for the QRS complex and 99.21% and 99.85% for the T wave. For the critera of average error and standard deviation, our method has the performance similar to those methods. In addition, our algorithm can also handle such several situations where the boundary determination of crucial waves is tough as high T wave, high noise and baseline wandering well.
format	article
author	Genlang Chen Maolin Chen Jiajian Zhang Liang Zhang Chaoyi Pang
author_facet	Genlang Chen Maolin Chen Jiajian Zhang Liang Zhang Chaoyi Pang
author_sort	Genlang Chen
title	A Crucial Wave Detection and Delineation Method for Twelve-Lead ECG Signals
title_short	A Crucial Wave Detection and Delineation Method for Twelve-Lead ECG Signals
title_full	A Crucial Wave Detection and Delineation Method for Twelve-Lead ECG Signals
title_fullStr	A Crucial Wave Detection and Delineation Method for Twelve-Lead ECG Signals
title_full_unstemmed	A Crucial Wave Detection and Delineation Method for Twelve-Lead ECG Signals
title_sort	crucial wave detection and delineation method for twelve-lead ecg signals
publisher	IEEE
publishDate	2020
url	https://doaj.org/article/bce6402565e1471bb4774c54176e3720
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A Crucial Wave Detection and Delineation Method for Twelve-Lead ECG Signals

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