2021
DOI: 10.1152/japplphysiol.00333.2020
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Characterizing cardiorespiratory interaction in preterm infants across sleep states using visibility graph analysis

Abstract: Cardiorespiratory interaction (CRI) has been intensively studied in adult sleep, yet not in preterm infants, in particular across different sleep states including wake (W), active sleep (AS), and quiet sleep (QS). The aim of this study was to quantify the interaction between cardiac and respiratory activities in different sleep states of preterm infants. The postmenstrual age (PMA) of preterm infants was also taken into consideration. The CRI during sleep was analyzed using a visibility graph (VG) method, enab… Show more

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Cited by 8 publications
(13 citation statements)
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“…Several parameters of the visibility graph network topology constructed from the cardiorespiratory interaction time series exhibited significant differences among the preterm infant sleep states. 15 Therefore, we extracted eight features from the cardiorespiratory interaction signals. The means and standard deviations of the degree of the cardiorespiratory interaction network were constructed using the visibility graph method and the network created with the difference visibility graph 22 was calculated.…”
Section: Featuresmentioning
confidence: 99%
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“…Several parameters of the visibility graph network topology constructed from the cardiorespiratory interaction time series exhibited significant differences among the preterm infant sleep states. 15 Therefore, we extracted eight features from the cardiorespiratory interaction signals. The means and standard deviations of the degree of the cardiorespiratory interaction network were constructed using the visibility graph method and the network created with the difference visibility graph 22 was calculated.…”
Section: Featuresmentioning
confidence: 99%
“…The assortative coefficient is a measure of assortative mixing by degree and it represents the skewness in the connections of network nodes. 15 The clustering coefficient quantified the density of the local clusters within a network. The means and standard deviations of the clustering coefficient values were calculated for each epoch.…”
Section: Featuresmentioning
confidence: 99%
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