-
Something wrong with this record ?
A Comparative Analysis of Methods for Evaluation of ECG Signal Quality after Compression
A. Němcová, R. Smíšek, L. Maršánová, L. Smital, M. Vítek,
Language English Country United States
Document type Journal Article, Review
NLK
Free Medical Journals
from 2013
PubMed Central
from 2013
Europe PubMed Central
from 2013
ProQuest Central
from 2013
Open Access Digital Library
from 2001-01-01
Open Access Digital Library
from 2012-12-04
Open Access Digital Library
from 2013-01-01
CINAHL Plus with Full Text (EBSCOhost)
from 2013-01-01
Medline Complete (EBSCOhost)
from 2013-01-01
Health & Medicine (ProQuest)
from 2013
Wiley-Blackwell Open Access Titles
from 2001
ROAD: Directory of Open Access Scholarly Resources
from 2013
PubMed
30112363
DOI
10.1155/2018/1868519
Knihovny.cz E-resources
- MeSH
- Algorithms MeSH
- Databases, Factual MeSH
- Electrocardiography * MeSH
- Data Compression MeSH
- Signal Processing, Computer-Assisted * MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
The assessment of ECG signal quality after compression is an essential part of the compression process. Compression facilitates the signal archiving, speeds up signal transmission, and reduces the energy consumption. Conversely, lossy compression distorts the signals. Therefore, it is necessary to express the compression performance through both compression efficiency and signal quality. This paper provides an overview of objective algorithms for the assessment of both ECG signal quality after compression and compression efficiency. In this area, there is a lack of standardization, and there is no extensive review as such. 40 methods were tested in terms of their suitability for quality assessment. For this purpose, the whole CSE database was used. The tested signals were compressed using an algorithm based on SPIHT with varying efficiency. As a reference, compressed signals were manually assessed by two experts and classified into three quality groups. Owing to the experts' classification, we determined corresponding ranges of selected quality evaluation methods' values. The suitability of the methods for quality assessment was evaluated based on five criteria. For the assessment of ECG signal quality after compression, we recommend using a combination of these methods: PSim SDNN, QS, SNR1, MSE, PRDN1, MAX, STDERR, and WEDD SWT.
References provided by Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc19000461
- 003
- CZ-PrNML
- 005
- 20250507093620.0
- 007
- ta
- 008
- 190107e20180718xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1155/2018/1868519 $2 doi
- 035 __
- $a (PubMed)30112363
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Němcová, Andrea $u Department of Biomedical Engineering, The Faculty of Electrical Engineering and Communication, Brno University of Technology, Technická 12, 616 00 Brno, Czech Republic. $7 xx0331813
- 245 12
- $a A Comparative Analysis of Methods for Evaluation of ECG Signal Quality after Compression / $c A. Němcová, R. Smíšek, L. Maršánová, L. Smital, M. Vítek,
- 520 9_
- $a The assessment of ECG signal quality after compression is an essential part of the compression process. Compression facilitates the signal archiving, speeds up signal transmission, and reduces the energy consumption. Conversely, lossy compression distorts the signals. Therefore, it is necessary to express the compression performance through both compression efficiency and signal quality. This paper provides an overview of objective algorithms for the assessment of both ECG signal quality after compression and compression efficiency. In this area, there is a lack of standardization, and there is no extensive review as such. 40 methods were tested in terms of their suitability for quality assessment. For this purpose, the whole CSE database was used. The tested signals were compressed using an algorithm based on SPIHT with varying efficiency. As a reference, compressed signals were manually assessed by two experts and classified into three quality groups. Owing to the experts' classification, we determined corresponding ranges of selected quality evaluation methods' values. The suitability of the methods for quality assessment was evaluated based on five criteria. For the assessment of ECG signal quality after compression, we recommend using a combination of these methods: PSim SDNN, QS, SNR1, MSE, PRDN1, MAX, STDERR, and WEDD SWT.
- 650 _2
- $a algoritmy $7 D000465
- 650 _2
- $a komprese dat $7 D044962
- 650 _2
- $a databáze faktografické $7 D016208
- 650 12
- $a elektrokardiografie $7 D004562
- 650 12
- $a počítačové zpracování signálu $7 D012815
- 655 _2
- $a časopisecké články $7 D016428
- 655 _2
- $a přehledy $7 D016454
- 700 1_
- $a Smíšek, Radovan $u Department of Biomedical Engineering, The Faculty of Electrical Engineering and Communication, Brno University of Technology, Technická 12, 616 00 Brno, Czech Republic. Institute of Scientific Instruments, The Czech Academy of Sciences, Královopolská 147, 612 64 Brno, Czech Republic.
- 700 1_
- $a Maršánová, Lucie $u Department of Biomedical Engineering, The Faculty of Electrical Engineering and Communication, Brno University of Technology, Technická 12, 616 00 Brno, Czech Republic.
- 700 1_
- $a Smital, Lukáš $u Department of Biomedical Engineering, The Faculty of Electrical Engineering and Communication, Brno University of Technology, Technická 12, 616 00 Brno, Czech Republic.
- 700 1_
- $a Vítek, Martin $u Department of Biomedical Engineering, The Faculty of Electrical Engineering and Communication, Brno University of Technology, Technická 12, 616 00 Brno, Czech Republic.
- 773 0_
- $w MED00182164 $t BioMed research international $x 2314-6141 $g Roč. 2018 (20180718), s. 1868519
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/30112363 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y a $z 0
- 990 __
- $a 20190107 $b ABA008
- 991 __
- $a 20250507093618 $b ABA008
- 999 __
- $a ok $b bmc $g 1363850 $s 1038584
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2018 $b 2018 $c - $d 1868519 $e 20180718 $i 2314-6141 $m BioMed research international $n Biomed Res Int $x MED00182164
- LZP __
- $a Pubmed-20190107