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Quantification of cardio-respiratory interactions in healthy children during night-time sleep using joint symbolic

Muammar M Kabir1, Mark Kohler, Derek Abbott

  • 1School of Electrical and Electronic Engineering, University of Adelaide, SA 5005, Australia. muammar.kabir@adelaide.edu.au

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed

Insights

Healthy children show stronger cardio-respiratory interactions during slow-wave sleep. Joint symbolic dynamics effectively analyzes these connections, unaffected by age, gender, or BMI.

Area of Science:

  • Cardiology
  • Sleep Medicine
  • Biomedical Engineering

Background:

  • Cardio-respiratory interactions are crucial for physiological regulation during sleep.
  • Understanding these interactions in children is vital for identifying potential health issues.
  • Traditional methods may not fully capture the complex dynamics of heart rate and respiration.

Purpose of the Study:

  • To investigate the relationship between R-R intervals and respiratory phases in healthy children during sleep.
  • To apply a novel joint symbolic dynamics technique for analyzing cardio-respiratory interactions.
  • To determine how sleep stages influence these interactions.

Main Methods:

  • Utilized overnight polysomnography data from 40 healthy children.
  • Extracted R-R interval time series from electrocardiograms (ECG).
  • Obtained respiratory phases using the Hilbert transform from abdominal sensors.
  • Transformed data into ternary symbol vectors and analyzed word correspondences for sleep stages.

Main Results:

  • A significantly higher percentage of similarity was observed in joint symbolic dynamics during slow-wave (SW) sleep.
  • This indicates a stronger cardio-respiratory interaction during SW sleep compared to other stages.
  • No significant effect of age, gender, or Body Mass Index (BMI) on cardio-respiratory interaction was found.

Conclusions:

  • Joint symbolic dynamics is a novel and efficient technique for analyzing cardio-respiratory interactions.
  • Cardio-respiratory coupling varies significantly across different sleep stages in children.
  • The findings provide new insights into sleep physiology and potential diagnostic tools.

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