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Cardiovascular and cardiorespiratory coupling analyses: a review.

Steffen Schulz¹, Felix-Constantin Adochiei, Ioana-Raluca Edu

¹Department of Medical Engineering and Biotechnology, University of Applied Sciences Jena, Jena, Germany.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|July 17, 2013

Summary

Nonlinear dynamics and information theory offer advanced methods to analyze complex interactions in cardiovascular and cardiorespiratory systems. These techniques reveal crucial insights into regulatory mechanisms for improved medical diagnostics and prognostics.

Keywords:

cardiorespiratory system cardiovascular system causality coupling direct coupling nonlinear

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Area of Science:

Biomedical Engineering
Nonlinear Dynamics
Information Theory

Background:

Growing interest in analyzing couplings within and between cardiovascular and cardiorespiratory systems.
Recognition that interactions between these regulatory mechanisms are likely nonlinear.
Limitations of traditional linear coupling analysis techniques in capturing complex biological interactions.

Purpose of the Study:

To review and describe commonly applied methods for detecting direct and indirect couplings between biological time series.
To focus on nonlinear approaches and their capacity to quantify interactions and their directionality.
To demonstrate the usefulness of these methods in cardiovascular and cardiorespiratory coupling analyses.

Main Methods:

Description of nonlinear methods including Granger causality, nonlinear prediction, entropy, symbolization, and phase synchronization.
Discussion of theoretical background, application requirements, and key features of each method.
Focus on multivariate analysis of information transfer between time series.

Main Results:

Nonlinear methods provide additional diagnostic and prognostic information compared to traditional linear techniques.
These approaches can quantify direct and indirect couplings and determine the driver-response relationship.
Demonstrated utility in various applications within cardiovascular and cardiorespiratory coupling analyses.

Conclusions:

Nonlinear dynamics and information theory offer powerful tools for understanding complex biological systems.
These advanced analytical methods can complement and enhance traditional coupling analysis in medicine.
Potential for improved insights into regulatory mechanisms in both healthy and diseased states.