Complexity-based analysis of the variations in brain activity in short deep breathing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F29142890%3A_____%2F25%3A00052460" target="_blank" >RIV/29142890:_____/25:00052460 - isvavai.cz</a>

Výsledek na webu

<a href="https://www-worldscientific-com.ezproxy.lib.cas.cz/doi/10.1142/S0218348X25500707" target="_blank" >https://www-worldscientific-com.ezproxy.lib.cas.cz/doi/10.1142/S0218348X25500707</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1142/S0218348X25500707" target="_blank" >10.1142/S0218348X25500707</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Complexity-based analysis of the variations in brain activity in short deep breathing

Popis výsledku v původním jazyce

Investigating the impact of deep breathing on brain activity is a crucial research area in biomedical science and engineering. In this paper, we examine the alterations in the complex structure of electroencephalogram (EEG) signals, which serve as indicators of brain activity, during rest and varying durations of short deep breathing exercises. We analyzed the fractal dimension (FD), approximate entropy (ApEn), and sample entropy (SampEn) of EEG signals during normal breathing, deep breathing sessions lasting 5, 7, and 9min, immediately after deep breathing, and in a follow-up session conducted seven days later. The findings revealed that for all durations of deep breathing, the complexity of EEG signals decreased compared to the pre-deep breathing (normal breathing) baseline. However, the complexity of EEG signals increased after the deep breathing sessions and continued to rise in the follow-up session. On the other hand, the longer duration of deep breathing causes greater decreases in the complexity of EEG signals during deep breathing, after that, and also in the follow-up session. This trend suggests that extended periods of deep breathing may lead to sustained changes in neural activity.

Název v anglickém jazyce

Complexity-based analysis of the variations in brain activity in short deep breathing

Popis výsledku anglicky

Investigating the impact of deep breathing on brain activity is a crucial research area in biomedical science and engineering. In this paper, we examine the alterations in the complex structure of electroencephalogram (EEG) signals, which serve as indicators of brain activity, during rest and varying durations of short deep breathing exercises. We analyzed the fractal dimension (FD), approximate entropy (ApEn), and sample entropy (SampEn) of EEG signals during normal breathing, deep breathing sessions lasting 5, 7, and 9min, immediately after deep breathing, and in a follow-up session conducted seven days later. The findings revealed that for all durations of deep breathing, the complexity of EEG signals decreased compared to the pre-deep breathing (normal breathing) baseline. However, the complexity of EEG signals increased after the deep breathing sessions and continued to rise in the follow-up session. On the other hand, the longer duration of deep breathing causes greater decreases in the complexity of EEG signals during deep breathing, after that, and also in the follow-up session. This trend suggests that extended periods of deep breathing may lead to sustained changes in neural activity.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10700 - Other natural sciences

Projekt

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Fractals - Complex Geometry Patterns and Scaling in Nature and Society

ISSN

0218-348X

e-ISSN

—

Svazek periodika

33

Číslo periodika v rámci svazku

09

Stát vydavatele periodika

SG - Singapurská republika

Počet stran výsledku

11

Strana od-do

—

Kód UT WoS článku

001520632700001

EID výsledku v databázi Scopus

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