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Related Experiment Videos

Progressive decrease of heart period variability entropy-based complexity during graded head-up tilt.

Alberto Porta1, Tomaso Gnecchi-Ruscone, Eleonora Tobaldini

  • 1Universita' degli Studi di Milano, Dipartimento di Tecnologie per la Salute, Istituto Ortopedico Galeazzi, Laboratorio di Modellistica di Sistemi Complessi, Via R. Galeazzi 4, 20161 Milan, Italy. alberto.porta@unimi.it

Journal of Applied Physiology (Bethesda, Md. : 1985)
|June 16, 2007
PubMed
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Heart rate variability complexity, measured by entropy rates, decreases with autonomic nervous system shifts during head-up tilt tests. These complexity measures offer insights into sympathovagal balance.

Area of Science:

  • Cardiovascular Physiology
  • Autonomic Nervous System Research
  • Biomedical Signal Processing

Background:

  • Heart rate variability (HRV) complexity is linked to aging and disease.
  • A direct relationship between HRV complexity and sympathovagal balance shifts has not been established.
  • Autonomic nervous system (ANS) activity influences cardiac regulation.

Purpose of the Study:

  • To investigate the relationship between HRV complexity and sympathovagal balance.
  • To evaluate established entropy-based complexity measures during a controlled autonomic challenge.
  • To determine if HRV complexity can serve as an index for monitoring ANS function.

Main Methods:

  • Analyzed short-term HRV series (approx. 250 beats) from 17 healthy subjects.

Related Experiment Videos

  • Utilized ECG recordings during a graded head-up tilt test (0-90 degrees inclination).
  • Calculated approximate entropy (ApEn), corrected ApEn, sample entropy (SampEn), and corrected conditional entropy (CCE) to assess HRV complexity.

    • Main Results:

    • Approximate entropy (ApEn) did not show significant changes during the tilt test.
    • Corrected ApEn, SampEn, and CCE demonstrated a progressive decrease in complexity with increasing tilt angle.
    • These findings suggest HRV complexity is modulated by the autonomic nervous system.

    Conclusions:

    • Entropy-based HRV complexity measures, particularly corrected versions, reflect changes in sympathovagal balance.
    • Corrected ApEn, SampEn, and CCE are valuable global indices for monitoring autonomic nervous system activity.
    • HRV complexity analysis provides a novel approach to understanding cardiovascular autonomic regulation.