ArticleFrontiers in physiology2020
Entropy Analysis of RR-Time Series From Stress Tests.
Article in Frontiers in physiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Characterizing infant leg movements using 72-h wearable sensor data: Descriptive analysis from a large, heterogenous sample of infants 0-2 months of age from the HEALthy Brain and Child Development Study.Infant behavior & development · 2026Article
- Autonomic impairment in advanced heart-failure patients revealed by nonlinear heart rate variability measured during exercise.Scientific reports · 2026Article
- Enhancing Physiological Complexity Through Mindfulness: A Wearable-Based Intervention for First Responders and Their Partners.Healthcare (Basel, Switzerland) · 2026Article
- Relationship between the autonomic nervous system and cerebral autoregulation during controlled breathing.European journal of applied physiology · 2026Article
- Analysis of Movement Variability During the Spike Jump Action in Young and High-Level Female Volleyball Players: Differences Between Categories and Playing Positions.Journal of functional morphology and kinesiology · 2025Article
- Utility of nonlinear analysis of heart rate variability in early detection of metabolic syndrome.Frontiers in physiology · 2025Article
- Entropy as a marker of physiological transition during pediatric cardiopulmonary exercise testing.Frontiers in physiology · 2025Article
- Dynamics of gas exchange and heart rate signal entropy in standard cardiopulmonary exercise testing during critical periods of growth and development.Physiological reports · 2024Article
- Automated classification of stress and relaxation responses in major depressive disorder, panic disorder, and healthy participants via heart rate variability.Frontiers in psychiatry · 2024Article
- Effect of Selected Music Soundtracks on Cardiac Vagal Control and Complexity Assessed by Heart Rate Variability.Physiological research · 2023Article
- Induced Relaxation Enhances the Cardiorespiratory Dynamics in COVID-19 Survivors.Entropy (Basel, Switzerland) · 2023Article
- Visibility Graph Analysis of Heartbeat Time Series: Comparison of Young vs. Old, Healthy vs. Diseased, Rest vs. Exercise, and Sedentary vs. Active.Entropy (Basel, Switzerland) · 2023Article
- The Fidget Factor and the obesity paradox. How small movements have big impact.Frontiers in sports and active living · 2023Article
- Acute Effects of Various Movement Noise in Differential Learning of Rope Skipping on Brain and Heart Recovery Analyzed by Means of Multiscale Fuzzy Measure Entropy.Frontiers in behavioral neuroscience · 2022Article
- Synchronization between music dynamics and heart rhythm is modulated by the musician's emotional involvement: A single case study.Frontiers in psychology · 2022Article
- Differences in heart rate variability and body composition in breast cancer survivors and women without cancer.Scientific reports · 2021Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The RR-interval time series or tachograms obtained from electrocardiograms have been widely studied since they reflect the cardiac variability, and this is an indicative of the health status of a person. The tachogram can be seen as a highly non-linear and complex time series, and therefore, should be analyzed with non-linear techniques. In this work, several entropy measures, Sample Entropy (SampEn), Approximate Entropy (ApEn), and Fuzzy Entropy (FuzzyEn) are used as a measure of heart rate variability (HRV). Tachograms belonging to thirty-nine subjects were obtained from a cardiac stress test consisting of a rest period followed by a period of moderate physical activity. Subjects are grouped according to their physical activity using the IPAQ sedentary and active questionnaire, we work with youth and middle-aged adults. The entropy measures for each group show that for the sedentary subjects the values are high at rest and decrease appreciably with moderate physical activity, This happens for both young and middle-aged adults. These results are highly reproducible. In the case of the subjects that exercise regularly, an increase in entropy is observed or they tend to retain the entropy value that they had at rest. It seems that there is a possible correlation between the physical condition of a person with the increase or decrease in entropy during moderate physical activity with respect to the entropy at rest. It was also observed that entropy during longer physical activity tests tends to decrease as fatigue accumulates, but this decrease is small compared to the change that occurs when going from rest to physical activity.
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