Complexity-based analysis of the variations in brain activity in short deep breathing
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Complexity-based analysis of the variations in brain activity in short deep breathing
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10700 - Other natural sciences
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Fractals - Complex Geometry Patterns and Scaling in Nature and Society
ISSN
0218-348X
e-ISSN
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Volume of the periodical
33
Issue of the periodical within the volume
09
Country of publishing house
SG - SINGAPORE
Number of pages
11
Pages from-to
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UT code for WoS article
001520632700001
EID of the result in the Scopus database
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