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Related Concept Videos

Pulse rhythm01:30

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Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
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Updated: Nov 27, 2025

Semi-automated Optical Heartbeat Analysis of Small Hearts
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Ordinal Patterns in Heartbeat Time Series: An Approach Using Multiscale Analysis.

María Muñoz-Guillermo1

  • 1Departamento de Matemática Aplicada y Estadística, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain.

Entropy (Basel, Switzerland)
|December 3, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces multiscale analysis of heartbeat time series using Rényi and weighted Rényi entropy. This method helps differentiate between healthy individuals and those with cardiac diseases by analyzing complexity dynamics.

Keywords:
heartbeat time seriesmultiscale analysisordinal patternsrényi entropy

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Area of Science:

  • Cardiology
  • Complex Systems
  • Information Theory

Background:

  • Heartbeat time series analysis is crucial for understanding cardiac health.
  • Traditional entropy measures may not fully capture the complexity of physiological signals.
  • Multiscale analysis offers a more comprehensive approach to signal complexity.

Purpose of the Study:

  • To introduce a novel multiscale analysis framework for heartbeat time series.
  • To measure the complexity of cardiac dynamics using Rényi and weighted Rényi entropy.
  • To differentiate between healthy subjects and cardiac disease patients using this method.

Main Methods:

  • Application of two different scales in ordinal pattern analysis.
  • Utilizing Rényi entropy and weighted Rényi entropy within a multiscale framework.
  • Involving four parameters in the multiscale analysis scheme.

Main Results:

  • Analysis of parameter variations on entropy values across different subject groups.
  • Demonstration of the effectiveness of multiscale analysis in detecting group differences.
  • Identification of distinct complexity patterns in heartbeat dynamics between healthy and diseased individuals.

Conclusions:

  • Multiscale entropy analysis provides a sensitive tool for cardiac health assessment.
  • The proposed method effectively distinguishes between healthy and cardiac disease groups.
  • This approach enhances the understanding of heartbeat time series complexity in clinical contexts.