Literature DB >> 3601474

Determination of sleep state in infants using respiratory variability.

G G Haddad, H J Jeng, T L Lai, R B Mellins.   

Abstract

Sleep staging has been conventionally performed using neurophysiologic and behavioral criteria. However, these criteria may not always be available. Since it is known that cardiorespiratory variables in rapid eye movement (REM) sleep are different from those in quiet sleep, we asked whether such variables can be used for the determination of sleep state. We studied nine normal full-term infants at 1 and 4 months of life. Ventilation was measured using barometric plethysmography and the RR interval using a high accuracy R wave detector. Electroencephalogram, electrooculogram, and postural muscle electromyogram were recorded using surface electrodes and behavioral criteria applied. Means of RR interval, respiratory cycle time and tidal volume, and coefficients of variation of the same variables, were obtained for 30-s intervals throughout each sleep study. The Kolmogorov-Smirnov distances between REM and quiet sleep were larger for the coefficients of variation than for the means at both ages for all variables. Moreover, coefficient of variation of respiratory cycle time was found to provide the largest separation between REM and quiet sleep. In view of this result, we developed a statistical decision rule using coefficient of variation of respiratory cycle time for the classification of REM and quiet sleep in blocks of 5-min periods. Each study was divided into 5-min epochs and this rule was applied to each epoch. Of 85 epochs staged as quiet sleep by neurophysiologic and behavioral criteria, 79 epochs (or 93%) were classified correctly as quiet sleep using our decision rule. Of 85 epochs staged as REM sleep, 84 were classified as REM sleep and only one misclassified as quiet sleep.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1987        PMID: 3601474     DOI: 10.1203/00006450-198706000-00010

Source DB:  PubMed          Journal:  Pediatr Res        ISSN: 0031-3998            Impact factor:   3.756


  7 in total

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2.  Application of recurrence quantification analysis to automatically estimate infant sleep states using a single channel of respiratory data.

Authors:  Philip I Terrill; Stephen J Wilson; Sadasivam Suresh; David M Cooper; Carolyn Dakin
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3.  An automated method for coding sleep states in human infants based on respiratory rate variability.

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Review 4.  Temporal variations in the pattern of breathing: techniques, sources, and applications to translational sciences.

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Journal:  J Physiol Sci       Date:  2022-08-29       Impact factor: 2.257

5.  Neonatal eyelid conditioning during sleep.

Authors:  Amanda R Tarullo; Joseph R Isler; Carmen Condon; Kimon Violaris; Peter D Balsam; William P Fifer
Journal:  Dev Psychobiol       Date:  2016-11       Impact factor: 3.038

6.  Behavioral and respiratory characteristics during sleep in neonatal DBA/2J and A/J mice.

Authors:  Alexander Balbir; Boris Lande; Robert S Fitzgerald; Vsevolod Polotsky; Wayne Mitzner; Machiko Shirahata
Journal:  Brain Res       Date:  2008-09-13       Impact factor: 3.252

7.  An Open Source Classifier for Bed Mattress Signal in Infant Sleep Monitoring.

Authors:  Jukka Ranta; Manu Airaksinen; Turkka Kirjavainen; Sampsa Vanhatalo; Nathan J Stevenson
Journal:  Front Neurosci       Date:  2021-01-14       Impact factor: 4.677

  7 in total

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