Computer classification of state in healthy preterm neonates.

Journal Article (Journal Article)

Nineteen electroencephalographic (EEG) sleep measures describing four physiologic aspects of sleep behavior (i.e. sleep continuity, EEG spectra, body and eye movements, and autonomic measures) were derived from visual and computer analyses of 71 24-channel, 3-hour EEG sleep recordings on 52 healthy preterm neonates from 28-36.5 weeks postconceptional age (PCA). Forty-eight subjects were neurodevelopmentally normal up to 2 years of age. Four electrographic states that comprise tracé discontinu of the preterm neonate were defined in terms of increasing seconds of EEG quiescence per minute. A regression analysis was performed after transformations of nonlinear data sets representing the 19 EEG sleep measures, with the four sleep states as outcome variables. Postconceptional age was also included in these analyses as the 20th explanatory variable. Four measures best defined the EEG sleep states, explaining 75% of the variance: decreasing rapid eye movements per minute, decreasing numbers of spontaneous arousals per minute, increasing spectral theta energies, and decreasing facial movements per minute. Other cerebral and noncerebral measures, including total spectral EEG energies, spectral EEG energies in three bandwidths (i.e. delta, alpha, beta), cardiac and respiratory measures, and body movements, did not contribute as significantly to the prediction. Inclusion of PCA into the regression equation with the four EEG measures, selected by the analysis procedure, indicated that its contribution to state prediction was also small; the effect of PCA on state was found to be explained by the four EEG sleep measures.

Full Text

Duke Authors

Cited Authors

  • Scher, MS; Dokianakis, SG; Steppe, DA; Banks, DL; Sclabassi, RJ

Published Date

  • February 1997

Published In

Volume / Issue

  • 20 / 2

Start / End Page

  • 132 - 141

PubMed ID

  • 9143073

Electronic International Standard Serial Number (EISSN)

  • 1550-9109

International Standard Serial Number (ISSN)

  • 0161-8105

Digital Object Identifier (DOI)

  • 10.1093/sleep/20.2.132


  • eng