Cardiovascular regulation during sleep quantified by symbolic coupling traces

Chaos. 2010 Dec;20(4):045124. doi: 10.1063/1.3518688.

Abstract

Sleep is a complex regulated process with short periods of wakefulness and different sleep stages. These sleep stages modulate autonomous functions such as blood pressure and heart rate. The method of symbolic coupling traces (SCT) is used to analyze and quantify time-delayed coupling of these measurements during different sleep stages. The symbolic coupling traces, defined as the symmetric and diametric traces of the bivariate word distribution matrix, allow the quantification of time-delayed coupling. In this paper, the method is applied to heart rate and systolic blood pressure time series during different sleep stages for healthy controls as well as for normotensive and hypertensive patients with sleep apneas. Using the SCT, significant different cardiovascular mechanisms not only between the deep sleep and the other sleep stages but also between healthy subjects and patients can be revealed. The SCT method is applied to model systems, compared with established methods, such as cross correlation, mutual information, and cross recurrence analysis and demonstrates its advantages especially for nonstationary physiological data. As a result, SCT proves to be more specific in detecting delays of directional interactions than standard coupling analysis methods and yields additional information which cannot be measured by standard parameters of heart rate and blood pressure variability. The proposed method may help to indicate the pathological changes in cardiovascular regulation and also the effects of continuous positive airway pressure therapy on the cardiovascular system.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Blood Pressure / physiology
  • Cardiovascular Physiological Phenomena*
  • Case-Control Studies
  • Humans
  • Male
  • Models, Cardiovascular*
  • Sleep / physiology*
  • Sleep Stages / physiology
  • Systole / physiology
  • Time Factors