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Updated: Nov 15, 2025

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Short-Term HRV Analysis Using Nonparametric Sample Entropy for Obstructive Sleep Apnea.

Duan Liang1,2,3, Shan Wu1,2,3, Lan Tang1,2,3

  • 1School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou 510275, China.

Entropy (Basel, Switzerland)
|March 6, 2021
PubMed
Summary
This summary is machine-generated.

Nonparametric sample entropy (NPSampEn) offers improved analysis of heart rate variability (HRV) for obstructive sleep apnea (OSA) detection. This novel index shows higher accuracy and stronger AHI correlation than traditional methods.

Keywords:
heart rate variability (HRV)nonparametric sample entropy (NPSampEn)obstructive sleep apnea (OSA)short-term HRV analysis

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Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Sleep Medicine

Background:

  • Obstructive sleep apnea (OSA) is linked to reduced heart rate variability (HRV) and autonomic dysfunction.
  • Sample entropy (SampEn) is a common HRV regularity analysis tool but struggles with short-term data due to parameter dependence.

Purpose of the Study:

  • To introduce and evaluate nonparametric sample entropy (NPSampEn) as a novel index for short-term HRV analysis in OSA.
  • To compare NPSampEn's performance against traditional SampEn and frequency domain indices for OSA detection.

Main Methods:

  • Utilized 60 6-hour ECG recordings from PhysioNet database (20 healthy, 14 mild-moderate OSA, 26 severe OSA).
  • Analyzed HRV using NPSampEn, SampEn, and LF/HF ratio.
  • Compared group differentiation, OSA screening accuracy, and correlation with apnea-hypopnea index (AHI).

Main Results:

  • NPSampEn significantly differentiated between healthy, mild-moderate, and severe OSA groups (p < 0.01).
  • NPSampEn achieved higher OSA screening accuracy (83.3%) compared to LF/HF (73.3%) and SampEn (68.3%).
  • NPSampEn demonstrated a stronger association with AHI (|r| = 0.756, p < 0.05) than SampEn (|r| = 0.602, p < 0.05).

Conclusions:

  • NPSampEn effectively overcomes individual differences in biomedical signal processing.
  • NPSampEn shows promise for analyzing short-term HRV segments, improving OSA detection and characterization.