Robust removal of short-duration artifacts in long neonatal EEG recordings using wavelet-enhanced ICA and adaptive combining of tentative reconstructions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F12%3A00194508" target="_blank" >RIV/68407700:21340/12:00194508 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985556:_____/12:00379312 RIV/68407700:21460/12:00194508 RIV/00064211:_____/12:#0000216

Výsledek na webu

<a href="http://iopscience.iop.org/0967-3334/33/8/N39/" target="_blank" >http://iopscience.iop.org/0967-3334/33/8/N39/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/0967-3334/33/8/N39" target="_blank" >10.1088/0967-3334/33/8/N39</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Robust removal of short-duration artifacts in long neonatal EEG recordings using wavelet-enhanced ICA and adaptive combining of tentative reconstructions

Popis výsledku v původním jazyce

The goal of this paper is to describe a robust artifact removal (RAR) method, an automatic sequential procedure which is capable of removing short-duration, high-amplitude artifacts from long-term neonatal EEG recordings. Such artifacts are mainly causedby movement activity, and have an adverse effect on the automatic processing of long-term sleep recordings. The artifacts are removed sequentially in short-term signals using independent component analysis (ICA) transformation and wavelet denoising. Inorder to gain robustness of the RAR method, the whole EEG recording is processed multiple times. The resulting tentative reconstructions are then combined. We show results in a data set of signals from ten healthy newborns. Those results prove, both qualitatively and quantitatively, that the RAR method is capable of automatically rejecting the mentioned artifacts without changes in overall signal properties such as the spectrum. The method is shown to perform better than either the wavel

Název v anglickém jazyce

Robust removal of short-duration artifacts in long neonatal EEG recordings using wavelet-enhanced ICA and adaptive combining of tentative reconstructions

Popis výsledku anglicky

The goal of this paper is to describe a robust artifact removal (RAR) method, an automatic sequential procedure which is capable of removing short-duration, high-amplitude artifacts from long-term neonatal EEG recordings. Such artifacts are mainly causedby movement activity, and have an adverse effect on the automatic processing of long-term sleep recordings. The artifacts are removed sequentially in short-term signals using independent component analysis (ICA) transformation and wavelet denoising. Inorder to gain robustness of the RAR method, the whole EEG recording is processed multiple times. The resulting tentative reconstructions are then combined. We show results in a data set of signals from ten healthy newborns. Those results prove, both qualitatively and quantitatively, that the RAR method is capable of automatically rejecting the mentioned artifacts without changes in overall signal properties such as the spectrum. The method is shown to perform better than either the wavel

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

FH - Neurologie, neurochirurgie, neurovědy

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Physiological Measurement

ISSN

0967-3334

e-ISSN

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Svazek periodika

33

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

11

Strana od-do

"N39"-"N49"

Kód UT WoS článku

000306760300001

EID výsledku v databázi Scopus

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