PEDIATRICS AND SLEEP - COMPUTER CLASSIFICATION OF STATE IN HEALTHY PRETERM NEONATES

Nineteen electroencephalographic (EEG) sleep measures describing four physiologic aspects of sleep behavior (i.e. sleep continuity, EEG spec tra, body and eye movements, and autonomic measures) were derived from visual and computer analyses of 71 24-channel, 3-hour EEG sleep recor dings on 52 healthy preterm neonates from 28-36.5 weeks postconception al age (PCA). Forty-eight subjects were neurodevelopmentally normal up to 2 years of age. Four electrographic states that comprise trace dis continu of the preterm neonate were defined in terms of increasing sec onds 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. Postc onceptional age was also included in these analyses as the 20th explan atory variable. Four measures best defined the EEG sleep states, expla ining 75% of the variance: decreasing rapid eye movements per minute, decreasing numbers of spontaneous arousals per minute, increasing spec tral theta energies, and decreasing facial movements per minute. Other cerebral and noncerebral measures, including total spectral EEG energ ies. spectral EEG energies in three bandwidths (i.e. delta. alpha, bet a), cardiac and respiratory measures, and body movements, did not cont ribute as significantly to the prediction. Inclusion of PCA into the r egression equation with the four EEG measures, selected by the analysi s procedure, indicated that its contribution to state prediction was a lso small. the effect of PCA on state was found to be explained by the four EEG sleep measures.