Literature DB >> 19963673

Characterising infant inter-breath interval patterns during active and quiet sleep using recurrence plot analysis.

Philip I Terrill1, Stephen J Wilson, Sadasivam Suresh, David M Cooper.   

Abstract

Breathing patterns are characteristically different between active and quiet sleep states in infants. It has been previously identified that breathing dynamics are governed by a non-linear controller which implies the need for a nonlinear analytical tool. Further, it has been shown that quantified nonlinear variables are different between adult sleep states. This study aims to determine whether a nonlinear analytical tool known as recurrence plot analysis can characterize breath intervals of active and quiet sleep states in infants. Overnight polysomnograms were obtained from 32 healthy infants. The 6 longest periods each of active and quiet sleep were identified and a software routine extracted inter-breath interval data for recurrence plot analysis. Determinism (DET), laminarity (LAM) and radius (RAD) values were calculated for an embedding dimension of 4, 6, 8 and 16, and fixed recurrence of 0.5, 1, 2, 3.5 and 5%. Recurrence plots exhibited characteristically different patterns for active and quiet sleep. Active sleep periods typically had higher values of RAD, DET and LAM than for quiet sleep, and this trend was invariant to a specific choice of embedding dimension or fixed recurrence. These differences may provide a basis for automated sleep state classification, and the quantitative investigation of pathological breathing patterns.

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Year:  2009        PMID: 19963673     DOI: 10.1109/IEMBS.2009.5332480

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  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
Journal:  Med Biol Eng Comput       Date:  2012-05-22       Impact factor: 2.602

2.  An automated method for coding sleep states in human infants based on respiratory rate variability.

Authors:  Joseph R Isler; Tracy Thai; Michael M Myers; William P Fifer
Journal:  Dev Psychobiol       Date:  2016-10-20       Impact factor: 3.038

  2 in total

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