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Coupling patterns between spontaneous rhythms and respiration in cardiovascular variability signals.
F Censi1, G Calcagnini, S Cerutti
1Department of Computer and System Sciences, University of Rome La Sapienza Via Nino Martoglio 5, 00137, Italy. censi@dis.uniromal.it
Computer Methods and Programs in Biomedicine
|March 12, 2002
Summary
This study quantifies the non-linear coupling between respiration and heart rate/blood pressure rhythms using Recurrence Quantification Analysis (RQA). Findings reveal stronger coupling at specific respiratory frequencies, suggesting potential for autonomic nervous system (ANS) analysis.
Area of Science:
- Physiology
- Non-linear dynamics
- Biomedical engineering
Background:
- Respiration and heart rate/blood pressure variability exhibit complex interactions.
- Understanding these coupling patterns is crucial for assessing autonomic nervous system (ANS) function.
- Recurrence Quantification Analysis (RQA) offers a method to quantify non-linear dynamics.
Purpose of the Study:
- To quantitatively assess the non-linear coupling patterns between respiratory and spontaneous heart rate and blood pressure variability rhythms.
- To investigate how different respiratory frequencies influence these coupling dynamics.
- To explore the potential clinical applications of RQA in analyzing ANS pathologies.
Main Methods:
- Quantitative study using Recurrence Quantification Analysis (RQA).
- Application of RQA to simulated and experimental data from ten healthy subjects.
- Data collected during controlled breathing at three distinct frequencies (0.25 Hz, 0.20 Hz, 0.13 Hz).
Main Results:
- RQA successfully quantified varying degrees of non-linear coupling and interference patterns.
- Higher non-linear coupling was observed when respiratory frequency was near the spontaneous Low Frequency (LF) rhythm (0.13 Hz) or twice the LF frequency (0.2 Hz).
- Weaker coupling was detected at a respiratory frequency of 0.25 Hz.
Conclusions:
- The study demonstrates RQA's capability to reveal intricate coupling dynamics between cardiorespiratory rhythms.
- Specific respiratory frequencies significantly modulate the non-linear coupling, particularly around the LF rhythm.
- Future clinical applications may involve targeted experimental protocols for ANS assessment and pathology analysis.