Pathologies affect the performance of ECG signals compression

Abstract The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect...

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Autores principales:	Andrea Nemcova, Radovan Smisek, Martin Vitek, Marie Novakova
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f0a57693d6f0444689a72521c86311ab
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spelling	oai:doaj.org-article:f0a57693d6f0444689a72521c86311ab2021-12-02T14:59:15ZPathologies affect the performance of ECG signals compression10.1038/s41598-021-89817-w2045-2322https://doaj.org/article/f0a57693d6f0444689a72521c86311ab2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89817-whttps://doaj.org/toc/2045-2322Abstract The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect the efficiency and quality of compression. Single-cycle fractal-based compression algorithm and compression algorithm based on combination of wavelet transform and set partitioning in hierarchical trees are used to compress 125 15-leads ECG signals from CSE database. Rhythm and morphology of these signals are newly annotated as physiological or pathological. The compression performance results are statistically evaluated. Using both compression algorithms, physiological signals are compressed with better quality than pathological signals according to 8 and 9 out of 12 quality metrics, respectively. Moreover, it was statistically proven that pathological signals were compressed with lower efficiency than physiological signals. Signals with physiological rhythm and physiological morphology were compressed with the best quality. The worst results reported the group of signals with pathological rhythm and pathological morphology. This study is the first one which deals with effects of ECG pathologies on the performance of compression algorithms. Signal-by-signal rhythm and morphology annotations (physiological/pathological) for the CSE database are newly published.Andrea NemcovaRadovan SmisekMartin VitekMarie NovakovaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Andrea Nemcova Radovan Smisek Martin Vitek Marie Novakova Pathologies affect the performance of ECG signals compression
description	Abstract The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect the efficiency and quality of compression. Single-cycle fractal-based compression algorithm and compression algorithm based on combination of wavelet transform and set partitioning in hierarchical trees are used to compress 125 15-leads ECG signals from CSE database. Rhythm and morphology of these signals are newly annotated as physiological or pathological. The compression performance results are statistically evaluated. Using both compression algorithms, physiological signals are compressed with better quality than pathological signals according to 8 and 9 out of 12 quality metrics, respectively. Moreover, it was statistically proven that pathological signals were compressed with lower efficiency than physiological signals. Signals with physiological rhythm and physiological morphology were compressed with the best quality. The worst results reported the group of signals with pathological rhythm and pathological morphology. This study is the first one which deals with effects of ECG pathologies on the performance of compression algorithms. Signal-by-signal rhythm and morphology annotations (physiological/pathological) for the CSE database are newly published.
format	article
author	Andrea Nemcova Radovan Smisek Martin Vitek Marie Novakova
author_facet	Andrea Nemcova Radovan Smisek Martin Vitek Marie Novakova
author_sort	Andrea Nemcova
title	Pathologies affect the performance of ECG signals compression
title_short	Pathologies affect the performance of ECG signals compression
title_full	Pathologies affect the performance of ECG signals compression
title_fullStr	Pathologies affect the performance of ECG signals compression
title_full_unstemmed	Pathologies affect the performance of ECG signals compression
title_sort	pathologies affect the performance of ecg signals compression
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f0a57693d6f0444689a72521c86311ab
work_keys_str_mv	AT andreanemcova pathologiesaffecttheperformanceofecgsignalscompression AT radovansmisek pathologiesaffecttheperformanceofecgsignalscompression AT martinvitek pathologiesaffecttheperformanceofecgsignalscompression AT marienovakova pathologiesaffecttheperformanceofecgsignalscompression
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Pathologies affect the performance of ECG signals compression

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