NEMCOVA, Andrea, Radovan SMISEK, Martin VITEK and Marie NOVÁKOVÁ. Pathologies affect the performance of ECG signals compression. Scientific Reports. Berlin: Nature, 2021, vol. 11, No 1, p. 1-9. ISSN 2045-2322. Available from: https://dx.doi.org/10.1038/s41598-021-89817-w.
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Basic information
Original name Pathologies affect the performance of ECG signals compression
Authors NEMCOVA, Andrea (203 Czech Republic, guarantor), Radovan SMISEK (203 Czech Republic), Martin VITEK (203 Czech Republic) and Marie NOVÁKOVÁ (203 Czech Republic, belonging to the institution).
Edition Scientific Reports, Berlin, Nature, 2021, 2045-2322.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 30105 Physiology
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 4.996
RIV identification code RIV/00216224:14110/21:00121618
Organization unit Faculty of Medicine
Doi http://dx.doi.org/10.1038/s41598-021-89817-w
UT WoS 000658858700010
Keywords in English Pathologies; ECG signals compression
Tags 14110515, rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Tereza Miškechová, učo 341652. Changed: 29/6/2021 12:01.
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.
Links
MUNI/A/1246/2020, interní kód MUName: Kardiovaskulární systém: od iontového kanálu k celotělovému modelu (Acronym: KAVASYKAMO)
Investor: Masaryk University
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