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Related Experiment Videos

Recurrence-plot-based measures of complexity and their application to heart-rate-variability data.

Norbert Marwan1, Niels Wessel, Udo Meyerfeldt

  • 1Nonlinear Dynamics Group, Institute of Physics, University of Potsdam, Potsdam 14415, Germany. marwan@agnld.uni-potsdam.de

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 21, 2002
PubMed
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New complexity measures using vertical structures in recurrence plots can detect transitions in complex systems. This method identifies laminar phases in heart rate variability, potentially predicting life-threatening cardiac arrhythmias.

Area of Science:

  • Complex systems analysis
  • Nonlinear dynamics
  • Physiological signal processing

Background:

  • Understanding transitions between regular, laminar, and chaotic behaviors is crucial for complex systems.
  • Linear methods are often insufficient, and existing nonlinear methods require extensive time observations.
  • Recurrence quantification analysis (RQA) has limitations in detecting certain transitions.

Purpose of the Study:

  • To develop novel complexity measures based on vertical structures in recurrence plots.
  • To apply these measures to detect transitions in both model systems (logistic map) and real-world data (heart rate variability).
  • To overcome limitations of traditional methods in identifying specific types of transitions, such as chaos-chaos.

Main Methods:

  • Development of complexity measures utilizing vertical structures within recurrence plots.

Related Experiment Videos

  • Application of these measures to the logistic map to analyze transitions between chaotic and periodic states.
  • Analysis of heart rate variability (HRV) data to detect and quantify pre-arrhythmia phases.

    • Main Results:

    • The proposed measures successfully detect transitions between chaotic and periodic states in the logistic map.
    • Identification of laminar states (chaos-chaos transitions) in the logistic map, which traditional RQA fails to detect.
    • Detection and quantification of laminar phases in HRV data preceding life-threatening cardiac arrhythmias.

    Conclusions:

    • Novel complexity measures based on vertical recurrence plot structures offer enhanced capabilities for analyzing complex system dynamics.
    • These measures can identify previously undetectable chaos-chaos transitions, improving the understanding of system behavior.
    • Application to heart rate variability shows potential for predicting critical events like cardiac arrhythmias, aiding therapeutic strategies.