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Complexity quantification of cardiac variability time series using improved sample entropy (I-SampEn).

Puneeta Marwaha1, Ramesh Kumar Sunkaria2

  • 1Department of Electronics and Communication Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, 144011, India. puneetamarwaha@gmail.com.

Australasian Physical & Engineering Sciences in Medicine
|June 17, 2016
PubMed
Summary

Improved sample entropy (I-SampEn) enhances complexity analysis of heart rate variability. This new method accurately distinguishes healthy individuals from those with atrial fibrillation or diabetes by considering beat-to-beat variations.

Keywords:
Cardiovascular systemComplexityImproved sample entropy (I-SampEn)RR-interval time seriesSample entropy (SampEn)Variability

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Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Data Science

Background:

  • Sample entropy (SampEn) quantifies RR-interval time series complexity, with higher entropy indicating healthier subjects.
  • Existing SampEn methods inaccurately assign high entropy to pathological or randomized data due to reliance on long-term standard deviation.
  • This limitation hinders accurate complexity assessment in conditions with significant beat-to-beat variability.

Purpose of the Study:

  • To propose an improved sample entropy (I-SampEn) method for more accurate complexity quantification of RR-interval time series.
  • To address the limitations of standard SampEn by incorporating period-to-period variations in threshold calculation.
  • To validate I-SampEn's effectiveness in differentiating healthy subjects from patients with cardiovascular and non-cardiovascular diseases.

Main Methods:

  • Developed an improved sample entropy (I-SampEn) algorithm.
  • Modified the threshold updating mechanism to consider the standard deviation of the first-order difference (short-term SD) of the time series.
  • Applied I-SampEn to RR-interval time series from healthy subjects, patients with atrial fibrillation (AF), and diabetes mellitus (DM).

Main Results:

  • I-SampEn assigns higher entropy values to healthy subjects compared to patients with AF and DM.
  • The improved method demonstrates greater accuracy in reflecting the reduced complexity associated with these pathologies.
  • Results align with established theories on complexity reduction in chronic diseases affecting heart rate variability.

Conclusions:

  • The proposed I-SampEn method offers a more reliable measure of RR-interval time series complexity.
  • I-SampEn effectively distinguishes healthy individuals from those with AF and DM, reflecting disease-induced complexity changes.
  • This advancement has potential implications for diagnosing and monitoring cardiovascular and related chronic conditions.