COMPLEXITY-BASED ANALYSIS OF HEART RATE VARIABILITY DURING AGING
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F22%3A50019749" target="_blank" >RIV/62690094:18450/22:50019749 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.worldscientific.com/doi/10.1142/S0218348X22501985" target="_blank" >https://www.worldscientific.com/doi/10.1142/S0218348X22501985</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1142/S0218348X22501985" target="_blank" >10.1142/S0218348X22501985</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
COMPLEXITY-BASED ANALYSIS OF HEART RATE VARIABILITY DURING AGING
Popis výsledku v původním jazyce
One of the important areas of heart research is investigating how heart activity changes during aging. In this research, we employed complexity-based techniques to analyze how heart activity varies based on the age of subjects. For this purpose, the heart rate variability (HRV) of 54 healthy subjects (30 M, 24 F, 28.5-76 years old) in three different age groups was analyzed using fractal theory, sample entropy, and approximate entropy. We showed that the fractal dimension, sample entropy, and approximate entropy of the RR interval time series (as HRV) are related to the age of the subjects. In other words, as subjects get older, the complexity of their RR interval time series decreases. Therefore, we decoded the variations in HRV during aging. The method of analysis that was employed in this research can be used to analyze the variations of other physiological signals (e.g. Electroencephalogram (EEG) signals) during aging. © 2022
Název v anglickém jazyce
COMPLEXITY-BASED ANALYSIS OF HEART RATE VARIABILITY DURING AGING
Popis výsledku anglicky
One of the important areas of heart research is investigating how heart activity changes during aging. In this research, we employed complexity-based techniques to analyze how heart activity varies based on the age of subjects. For this purpose, the heart rate variability (HRV) of 54 healthy subjects (30 M, 24 F, 28.5-76 years old) in three different age groups was analyzed using fractal theory, sample entropy, and approximate entropy. We showed that the fractal dimension, sample entropy, and approximate entropy of the RR interval time series (as HRV) are related to the age of the subjects. In other words, as subjects get older, the complexity of their RR interval time series decreases. Therefore, we decoded the variations in HRV during aging. The method of analysis that was employed in this research can be used to analyze the variations of other physiological signals (e.g. Electroencephalogram (EEG) signals) during aging. © 2022
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10103 - Statistics and probability
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Fractals
ISSN
0218-348X
e-ISSN
1793-6543
Svazek periodika
30
Číslo periodika v rámci svazku
9
Stát vydavatele periodika
SG - Singapurská republika
Počet stran výsledku
8
Strana od-do
"Article number: 2250198"
Kód UT WoS článku
000911209100032
EID výsledku v databázi Scopus
2-s2.0-85143641343