Key result
Aging is associated with a decrease in the complexity of the RR interval time series, as measured by fractal dimension, sample entropy, and approximate entropy.
Why the study?
Investigating how heart activity changes during aging is an important area of heart research.
Does the complexity of heart rate variability decrease with aging in healthy subjects?
Cross-Sectional (n=54)
Does the complexity of heart rate variability decrease with aging in healthy subjects?
Heart rate variability complexity, measured via fractal dimension and entropy, decreases with healthy aging.
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.
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Dawi et al. (2022) conducted a cross-sectional in Healthy (n=54). Aging vs. Younger age groups was evaluated on Heart rate variability complexity (fractal dimension, sample entropy, approximate entropy). Aging is associated with a decrease in the complexity of the RR interval time series, as measured by fractal dimension, sample entropy, and approximate entropy.
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