Pathologies affect the performance of ECG signals compression

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dc.contributor.authorNěmcová, Andreacs
dc.contributor.authorSmíšek, Radovancs
dc.contributor.authorVítek, Martincs
dc.contributor.authorNováková, Mariecs
dc.coverage.issue1cs
dc.coverage.volume11cs
dc.date.accessioned2021-08-13T06:53:02Z
dc.date.available2021-08-13T06:53:02Z
dc.date.issued2021-05-18cs
dc.description.abstractThe 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.en
dc.formattextcs
dc.format.extent1-9cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationScientific Reports. 2021, vol. 11, issue 1, p. 1-9.en
dc.identifier.doi10.1038/s41598-021-89817-wcs
dc.identifier.issn2045-2322cs
dc.identifier.other171960cs
dc.identifier.urihttp://hdl.handle.net/11012/200967
dc.language.isoencs
dc.publisherSpringer Naturecs
dc.relation.ispartofScientific Reportscs
dc.relation.urihttps://www.nature.com/articles/s41598-021-89817-wcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2045-2322/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectannotationsen
dc.subjectcompressionen
dc.subjectECGen
dc.subjectelectrocardiogramen
dc.subjectfractal-based compressionen
dc.subjectmorphologyen
dc.subjectpathologyen
dc.subjectrhythmen
dc.subjectSPIHTen
dc.subjectwavelet transformen
dc.titlePathologies affect the performance of ECG signals compressionen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-171960en
sync.item.dbtypeVAVen
sync.item.insts2021.08.13 08:53:01en
sync.item.modts2021.08.13 08:14:26en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav biomedicínského inženýrstvícs
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