Publication detail

Pathologies affect the performance of ECG signals compression

NĚMCOVÁ, A. SMÍŠEK, R. VÍTEK, M. NOVÁKOVÁ, M.

Original Title

Pathologies affect the performance of ECG signals compression

Type

journal article in Web of Science

Language

English

Original 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.

Keywords

annotations; compression; ECG; electrocardiogram; fractal-based compression; morphology; pathology; rhythm; SPIHT; wavelet transform

Authors

NĚMCOVÁ, A.; SMÍŠEK, R.; VÍTEK, M.; NOVÁKOVÁ, M.

Released

18. 5. 2021

Publisher

Springer Nature

Location

BERLIN

ISBN

2045-2322

Periodical

Scientific Reports

Year of study

11

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

1

Pages to

9

Pages count

9

URL

https://www.nature.com/articles/s41598-021-89817-w

Full text in the Digital Library

http://hdl.handle.net/11012/200967

BibTex

@article{BUT171960,
  author="Andrea {Němcová} and Radovan {Smíšek} and Martin {Vítek} and Marie {Nováková}",
  title="Pathologies affect the performance of ECG signals compression",
  journal="Scientific Reports",
  year="2021",
  volume="11",
  number="1",
  pages="1--9",
  doi="10.1038/s41598-021-89817-w",
  issn="2045-2322",
  url="https://www.nature.com/articles/s41598-021-89817-w"
}