Complexity and information-based analysis of th electroencephalogram (EEG) signals in standing, walking, and walking with a brain-computer interface

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14510%2F22%3A00125421" target="_blank" >RIV/00216224:14510/22:00125421 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.worldscientific.com/doi/epdf/10.1142/S0218348X22500414" target="_blank" >https://www.worldscientific.com/doi/epdf/10.1142/S0218348X22500414</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1142/S0218348X22500414" target="_blank" >10.1142/S0218348X22500414</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Complexity and information-based analysis of th electroencephalogram (EEG) signals in standing, walking, and walking with a brain-computer interface

Popis výsledku v původním jazyce

In this paper, we analyzed the variations in brain activation between different activities. SinceElectroencephalogram (EEG) signals as an indicator of brain activation contain information andhave complex structures, we employed complexityand information-based analysis. Specifically,we used fractal theory and Shannon entropy for our analysis. Eight subjects performed threedifferent activities (standing, walking, and walking with a brain–computer interface) whiletheir EEG signals were recorded. Based on the results, the complexity and information contentof EEG signals have the greatest and smallest values in walking and standing, respectively.Complexity and information-based analysis can be applied to analyze the activations of otherorgans in different conditions.

Název v anglickém jazyce

Complexity and information-based analysis of th electroencephalogram (EEG) signals in standing, walking, and walking with a brain-computer interface

Popis výsledku anglicky

In this paper, we analyzed the variations in brain activation between different activities. SinceElectroencephalogram (EEG) signals as an indicator of brain activation contain information andhave complex structures, we employed complexityand information-based analysis. Specifically,we used fractal theory and Shannon entropy for our analysis. Eight subjects performed threedifferent activities (standing, walking, and walking with a brain–computer interface) whiletheir EEG signals were recorded. Based on the results, the complexity and information contentof EEG signals have the greatest and smallest values in walking and standing, respectively.Complexity and information-based analysis can be applied to analyze the activations of otherorgans in different conditions.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30103 - Neurosciences (including psychophysiology)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Fractals

ISSN

0218-348X

e-ISSN

1793-6543

Svazek periodika

30

Číslo periodika v rámci svazku

01

Stát vydavatele periodika

SG - Singapurská republika

Počet stran výsledku

7

Strana od-do

—

Kód UT WoS článku

000766635200037

EID výsledku v databázi Scopus

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