ArticleEntropy (Basel, Switzerland)2021
Short-Term HRV Analysis Using Nonparametric Sample Entropy for Obstructive Sleep Apnea.
Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed, 18 citations in OpenAlex.
- Complexity Analysis of Skin Nerve Activity for Quantitative Assessment of Acute Sympathetic Nervous System Activation.Sensors (Basel, Switzerland) · 2026Article
- Advancing entropy analysis for heart rate variability: clinical insights for aging and diabetes.Frontiers in physiology · 2026Review
- The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea.Frontiers in cardiovascular medicine · 2025Article
- Sensorimotor Cortical Activity during Respiratory Arousals in Obstructive Sleep Apnea.International journal of molecular sciences · 2022Article
- Fuzzy Approximate Entropy of Extrema Based on Multiple Moving Averages as a Novel Approach in Obstructive Sleep Apnea Screening.IEEE journal of translational engineering in health and medicine · 2022Article
- Assessment of Cardiorespiratory Interactions during Apneic Events in Sleep via Fuzzy Kernel Measures of Information Dynamics.Entropy (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obstructive sleep apnea (OSA) is associated with reduced heart rate variability (HRV) and autonomic nervous system dysfunction. Sample entropy (SampEn) is commonly used for regularity analysis. However, it has limitations in processing short-term segments of HRV signals due to the extreme dependence of its functional parameters. We used the nonparametric sample entropy (NPSampEn) as a novel index for short-term HRV analysis in the case of OSA. The manuscript included 60 6-h electrocardiogram recordings (20 healthy, 14 mild-moderate OSA, and 26 severe OSA) from the PhysioNet database. The NPSampEn value was compared with the SampEn value and frequency domain indices. The empirical results showed that NPSampEn could better differentiate the three groups (
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Registered trials
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