ArticleFrontiers in physiology2020
Maturation of the Autonomic Nervous System in Premature Infants: Estimating Development Based on Heart-Rate Variability Analysis.
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 8 papers.
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Who cites it
8 citing papers in PubMed, 21 citations in OpenAlex.
- Maturational physiology in preterm infants: morbidity impact and 2-year neurodevelopmental outcome.Pediatric research · 2026Article
- Autonomic nervous system maturation in preterm neonates: Correlation with gestational and postmenstrual age (ProMote).PloS one · 2026Article
- Sample entropy of oxygen saturation in preterm infants.Scientific reports · 2025Article
- Article
- Age-dependent patterns of cardiac complexity unveiled by topological data analysis of pediatric heart rate variability.PloS one · 2025Article
- Entropy Analysis of Heart Rate Variability in Different Sleep Stages.Entropy (Basel, Switzerland) · 2022Article
- Estimating Resting HRV during fMRI: A Comparison between Laboratory and Scanner Environment.Sensors (Basel, Switzerland) · 2021Article
- Research on Driving Fatigue Alleviation Using Interesting Auditory Stimulation Based on VMD-MMSE.Entropy (Basel, Switzerland) · 2021Article
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aims at investigating the development of premature infants' autonomic nervous system (ANS) based on a quantitative analysis of the heart-rate variability (HRV) with a variety of novel features. Additionally, the role of heart-rate drops, known as bradycardias, has been studied in relation to both clinical and novel sympathovagal indices. ECG data were measured for at least 3 h in 25 preterm infants (gestational age ≤32 weeks) for a total number of 74 recordings. The post-menstrual age (PMA) of each patient was estimated from the RR interval time-series by means of multivariate linear-mixed effects regression. The tachograms were segmented based on bradycardias in periods after, between and during bradycardias. For each of those epochs, a set of temporal, spectral and fractal indices were included in the regression model. The best performing model has
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