Sleep physiological network analysis in children

Alvaro David Orjuela-Cañón, Andrés Leonardo Jutinico, Maria Angelica Bazurto-Zapata, Elida Duenas-Meza

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: Physiological networks have recently been employed as an alternative to analyze the interaction of the human body. Within this option, different systems are analyzed as nodes inside a communication network as well how information flows. Several studies have been proposed to study sleep subjects with the help of the Granger causality computation over electroencephalographic and heart rate variability signals. However, following this methodology, novel approximations for children subjects are presented here, where comparison between adult and children sleep is followed through the obtained connectivities. Methods: Data from ten adults and children were retrospectively extracted from polysomnography records. Database was extracted from people suspected of having sleep disorders who participated in a previous study. Connectivity was computed based on Granger causality, according to preprocessing of similar studies in this field. A comparison for adults and children groups with a chi-square test was followed, employing the results of the Granger causality measures. Results: Results show that differences were mainly established for nodes inside the brain network connectivity. Additionally, for interactions between brain and heart networks, it was brought to light that children physiology sends more information from heart to brain nodes compared to the adults group. Discussion: This study represents a first sight to children sleep analysis, employing the Granger causality computation. It contributes to understand sleep in children employing measurements from physiological signals. Preliminary findings suggest more interactions inside the brain network for children group compared to adults group.

Original languageEnglish (US)
Pages (from-to)215-223
Number of pages9
JournalSleep Science
Volume15
DOIs
StatePublished - 2022

All Science Journal Classification (ASJC) codes

  • Neuroscience (miscellaneous)
  • Medicine (miscellaneous)
  • Behavioral Neuroscience

Author Keywords

  • Concept

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