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Related Experiment Video

Updated: Jun 5, 2026

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Published on: August 2, 2017

Cardiovascular regulation during sleep quantified by symbolic coupling traces.

A Suhrbier¹, M Riedl, H Malberg

¹Institute for Applied Computer Science, Forschungszentrum Karlsruhe GmbH (Karlsruhe Research Center), Karlsruhe Institute of Technology (KIT), Karlsruhe 76131, Germany.

Chaos (Woodbury, N.Y.)

|January 5, 2011

Summary

Symbolic coupling traces (SCT) reveal distinct cardiovascular regulation during sleep stages and in patients with sleep apnea. This novel method offers superior detection of directional interactions in physiological data.

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Area of Science:

Cardiovascular physiology
Sleep medicine
Biomedical signal processing

Background:

Sleep stages significantly influence autonomic functions like heart rate and blood pressure.
Understanding cardiovascular regulation during sleep is crucial for diagnosing and treating sleep-related disorders.
Existing methods for analyzing physiological time series have limitations with nonstationary data.

Purpose of the Study:

To introduce and validate the Symbolic Coupling Traces (SCT) method for analyzing cardiovascular regulation during sleep.
To quantify time-delayed coupling between heart rate and systolic blood pressure across different sleep stages.
To compare SCT with established methods for analyzing physiological data.

Main Methods:

Application of Symbolic Coupling Traces (SCT) to heart rate and systolic blood pressure time series.
Analysis of data from healthy controls and patients with sleep apnea during various sleep stages.
Comparison of SCT with cross-correlation, mutual information, and cross-recurrence analysis.

Main Results:

SCT revealed significant differences in cardiovascular mechanisms between sleep stages and between healthy subjects and patients.
The method demonstrated advantages over established techniques, particularly for nonstationary physiological data.
SCT showed higher specificity in detecting delayed directional interactions compared to standard coupling analysis.

Conclusions:

SCT is a powerful tool for uncovering pathological changes in cardiovascular regulation during sleep.
The method provides additional information beyond standard heart rate and blood pressure variability parameters.
SCT may aid in assessing the effects of therapies like continuous positive airway pressure (CPAP) on the cardiovascular system.