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Proposed corrections for the quantification of coupling patterns by recurrence plots
Federica Censi1, Giovanni Calcagnini, Sergio Cerutti
1Department of Computer and System Science, University of Rome La Sapienza, Roma, Italy. censi@iss.it
IEEE Transactions on Bio-Medical Engineering
|May 11, 2004
Summary
This study quantifies coupling in phase-locking patterns using recurrence plot quantification. Recurrence metrics effectively distinguished coupling conditions in simulated and cardiorespiratory synchronization data.
Area of Science:
- Complex systems analysis
- Nonlinear dynamics
- Physiological signal processing
Background:
- Phase-locking patterns are crucial in biological systems.
- Quantifying coupling strength in these patterns is challenging.
- Recurrence plot quantification (RPQ) offers a novel approach.
Purpose of the Study:
- To quantify coupling during phase-locking patterns.
- To evaluate the efficacy of RPQ in distinguishing coupling conditions.
- To apply RPQ to both simulated and real-world physiological data.
Main Methods:
- Utilized the recurrence plot quantification (RPQ) approach.
- Calculated percent determinism and entropy of recurrences.
- Applied corrections for border effects in finite datasets.
Main Results:
- RPQ successfully distinguished three distinct coupling conditions.
- Findings were consistent across simulated signals.
- RPQ effectively analyzed real cardiorespiratory synchronization data.
Conclusions:
- Recurrence plot quantification is a robust method for analyzing coupling in phase-locking patterns.
- Percent determinism and corrected recurrence entropy are key metrics for distinguishing coupling.
- This approach has significant applications in understanding cardiorespiratory synchronization.