NEW ALGORITHM FOR EEG AND EMG SEPARATION

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00235120" target="_blank" >RIV/68407700:21230/15:00235120 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

NEW ALGORITHM FOR EEG AND EMG SEPARATION

Popis výsledku v původním jazyce

The paper presents newly proposed algorithm for the blind separation of EEG and EMG sources measured by high density electrode arrays. The algorithm is based on the maximization of the variance of variances of filtered principal components. Utilized highpass filter was optimized in order to extract the information which is used by the gradient algorithm to separate New Algorithm for EEG and EMG SeparationEEG and EMG components. The performance of the algorithm was evaluated by its use for the muscularartifacts removal. Present muscular artifacts were extracted from the estimated components with the use of the previously used classifier. It is compared with other similar approaches and it is shown that the suggested algorithm achieves higher quality of the processed EEG signal especially in the case of strong muscular artifacts and is therefore useful for the preprocessing of the EEG records contaminated with the muscle activity.

Název v anglickém jazyce

NEW ALGORITHM FOR EEG AND EMG SEPARATION

Popis výsledku anglicky

The paper presents newly proposed algorithm for the blind separation of EEG and EMG sources measured by high density electrode arrays. The algorithm is based on the maximization of the variance of variances of filtered principal components. Utilized highpass filter was optimized in order to extract the information which is used by the gradient algorithm to separate New Algorithm for EEG and EMG SeparationEEG and EMG components. The performance of the algorithm was evaluated by its use for the muscularartifacts removal. Present muscular artifacts were extracted from the estimated components with the use of the previously used classifier. It is compared with other similar approaches and it is shown that the suggested algorithm achieves higher quality of the processed EEG signal especially in the case of strong muscular artifacts and is therefore useful for the preprocessing of the EEG records contaminated with the muscle activity.

Druh

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

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

<a href="/cs/project/GPP102%2F11%2FP109" target="_blank" >GPP102/11/P109: Techniky prostorové filtrace pro elektroencefalografické záznamy s vysokou hustotou elektrod</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Lékař a technika

ISSN

0301-5491

e-ISSN

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Svazek periodika

45

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

5

Strana od-do

43-47

Kód UT WoS článku

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EID výsledku v databázi Scopus

2-s2.0-84958037297