Independent Component Analysis and Decision Trees for ECG
Holter Recording De-Noising

J 2014

Independent Component Analysis and Decision Trees for ECG Holter Recording De-Noising

KUZILEK, Jakub; Vaclav KREMEN; Filip SOUČEK a Lenka LHOTSKA

Základní údaje

Originální název

Independent Component Analysis and Decision Trees for ECG Holter Recording De-Noising

Autoři

KUZILEK, Jakub (203 Česká republika); Vaclav KREMEN (203 Česká republika); Filip SOUČEK (203 Česká republika, garant, domácí) a Lenka LHOTSKA (203 Česká republika)

Vydání

Plos one, San Francisco, Public library science, 2014, 1932-6203

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30201 Cardiac and Cardiovascular systems

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 3.234

Kód RIV

RIV/00216224:14110/14:00078730

Organizační jednotka

Lékařská fakulta

DOI

http://dx.doi.org/10.1371/journal.pone.0098450

UT WoS

000341869000031

EID Scopus

2-s2.0-84902578838

Klíčová slova anglicky

ELECTROCARDIOGRAPHIC SIGNALS; REMOVING ARTIFACTS; REDUCTION; DATABASE; ALGORITHMS; DYNAMICS

Štítky

EL OK

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 27. 1. 2015 15:48, Soňa Böhmová

Anotace

V originále

We have developed a method focusing on ECG signal de-noising using Independent component analysis (ICA). This approach combines JADE source separation and binary decision tree for identification and subsequent ECG noise removal. In order to to test the efficiency of this method comparison to standard filtering a wavelet-based de-noising method was used. Freely data available at Physionet medical data storage were evaluated. Evaluation criteria was root mean square error (RMSE) between original ECG and filtered data contaminated with artificial noise. Proposed algorithm achieved comparable result in terms of standard noises (power line interference, base line wander, EMG), but noticeably significantly better results were achieved when uncommon noise (electrode cable movement artefact) were compared.

Citovat

KUZILEK, Jakub; Vaclav KREMEN; Filip SOUČEK a Lenka LHOTSKA. Independent Component Analysis and Decision Trees for ECG Holter Recording De-Noising. Plos one. San Francisco: Public library science, 2014, roč. 9, č. 6, s. "e98450", 9 s. ISSN 1932-6203. Dostupné z: https://dx.doi.org/10.1371/journal.pone.0098450.

@article{1218797,
   author = {Kuzilek, Jakub and Kremen, Vaclav and Souček, Filip and Lhotska, Lenka},
   article_location = {San Francisco},
   article_number = {6},
   doi = {http://dx.doi.org/10.1371/journal.pone.0098450},
   keywords = {ELECTROCARDIOGRAPHIC SIGNALS; REMOVING ARTIFACTS; REDUCTION; DATABASE; ALGORITHMS; DYNAMICS},
   language = {eng},
   issn = {1932-6203},
   journal = {Plos one},
   title = {Independent Component Analysis and Decision Trees for ECG Holter Recording De-Noising},
   volume = {9},
   year = {2014}
}

TY  - JOUR
ID  - 1218797
AU  - Kuzilek, Jakub - Kremen, Vaclav - Souček, Filip - Lhotska, Lenka
PY  - 2014
TI  - Independent Component Analysis and Decision Trees for ECG Holter Recording De-Noising
JF  - Plos one
VL  - 9
IS  - 6
SP  - "e98450"
EP  - "e98450"
PB  - Public library science
SN  - 19326203
KW  - ELECTROCARDIOGRAPHIC SIGNALS
KW  - REMOVING ARTIFACTS
KW  - REDUCTION
KW  - DATABASE
KW  - ALGORITHMS
KW  - DYNAMICS
N2  - We have developed a method focusing on ECG signal de-noising using Independent component analysis (ICA). This approach combines JADE source separation and binary decision tree for identification and subsequent ECG noise removal. In order to to test the efficiency of this method comparison to standard filtering a wavelet-based de-noising method was used. Freely data available at Physionet medical data storage were evaluated. Evaluation criteria was root mean square error (RMSE) between original ECG and filtered data contaminated with artificial noise. Proposed algorithm achieved comparable result in terms of standard noises (power line interference, base line wander, EMG), but noticeably significantly better results were achieved when uncommon noise (electrode cable movement artefact) were compared.
ER  -

KUZILEK, Jakub; Vaclav KREMEN; Filip SOUČEK a Lenka LHOTSKA. Independent Component Analysis and Decision Trees for ECG Holter Recording De-Noising. \textit{Plos one}. San Francisco: Public library science, 2014, roč.~9, č.~6, s.~''e98450'', 9 s. ISSN~1932-6203. Dostupné z: https://dx.doi.org/10.1371/journal.pone.0098450.

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