The hidden waves in the ECG uncovered revealing a sound automated interpretation method

Abstract A novel approach for analysing cardiac rhythm data is presented in this paper. Heartbeats are decomposed into the five fundamental P, Q, R, S and T waves plus an error term to account for artifacts in the data which provides a meaningful, physical interpretation of the heart’s electric syst...

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Autores principales:	Cristina Rueda, Yolanda Larriba, Adrian Lamela
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b37c99ed5c4341f8a9114b228e0c5c6a
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spelling	oai:doaj.org-article:b37c99ed5c4341f8a9114b228e0c5c6a2021-12-02T13:30:22ZThe hidden waves in the ECG uncovered revealing a sound automated interpretation method10.1038/s41598-021-82520-w2045-2322https://doaj.org/article/b37c99ed5c4341f8a9114b228e0c5c6a2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82520-whttps://doaj.org/toc/2045-2322Abstract A novel approach for analysing cardiac rhythm data is presented in this paper. Heartbeats are decomposed into the five fundamental P, Q, R, S and T waves plus an error term to account for artifacts in the data which provides a meaningful, physical interpretation of the heart’s electric system. The morphology of each wave is concisely described using four parameters that allow all the different patterns in heartbeats to be characterized and thus differentiated This multi-purpose approach solves such questions as the extraction of interpretable features, the detection of the fiducial marks of the fundamental waves, or the generation of synthetic data and the denoising of signals. Yet the greatest benefit from this new discovery will be the automatic diagnosis of heart anomalies as well as other clinical uses with great advantages compared to the rigid, vulnerable and black box machine learning procedures, widely used in medical devices. The paper shows the enormous potential of the method in practice; specifically, the capability to discriminate subjects, characterize morphologies and detect the fiducial marks (reference points) are validated numerically using simulated and real data, thus proving that it outperforms its competitors.Cristina RuedaYolanda LarribaAdrian LamelaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Cristina Rueda Yolanda Larriba Adrian Lamela The hidden waves in the ECG uncovered revealing a sound automated interpretation method
description	Abstract A novel approach for analysing cardiac rhythm data is presented in this paper. Heartbeats are decomposed into the five fundamental P, Q, R, S and T waves plus an error term to account for artifacts in the data which provides a meaningful, physical interpretation of the heart’s electric system. The morphology of each wave is concisely described using four parameters that allow all the different patterns in heartbeats to be characterized and thus differentiated This multi-purpose approach solves such questions as the extraction of interpretable features, the detection of the fiducial marks of the fundamental waves, or the generation of synthetic data and the denoising of signals. Yet the greatest benefit from this new discovery will be the automatic diagnosis of heart anomalies as well as other clinical uses with great advantages compared to the rigid, vulnerable and black box machine learning procedures, widely used in medical devices. The paper shows the enormous potential of the method in practice; specifically, the capability to discriminate subjects, characterize morphologies and detect the fiducial marks (reference points) are validated numerically using simulated and real data, thus proving that it outperforms its competitors.
format	article
author	Cristina Rueda Yolanda Larriba Adrian Lamela
author_facet	Cristina Rueda Yolanda Larriba Adrian Lamela
author_sort	Cristina Rueda
title	The hidden waves in the ECG uncovered revealing a sound automated interpretation method
title_short	The hidden waves in the ECG uncovered revealing a sound automated interpretation method
title_full	The hidden waves in the ECG uncovered revealing a sound automated interpretation method
title_fullStr	The hidden waves in the ECG uncovered revealing a sound automated interpretation method
title_full_unstemmed	The hidden waves in the ECG uncovered revealing a sound automated interpretation method
title_sort	hidden waves in the ecg uncovered revealing a sound automated interpretation method
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b37c99ed5c4341f8a9114b228e0c5c6a
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The hidden waves in the ECG uncovered revealing a sound automated interpretation method

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