Computer analyses of EEG-sleep in the neonate: methodological considerations.

Neonatal EEG interpretation can aid in the estimation of central nervous system maturation, as well as provide diagnostic and prognostic information of the high-risk infant. However, one cannot easily visualize the complex interrelationships coupling EEG and polysomnographic components of the EEG-sleep rhythm. This is particularly relevant for the preterm neonate, in whom a rudimentary sleep cycle has not yet been clearly delineated. Computer analysis can augment the information derived from the visual interpretation of scalp-generated EEG activity. Automated techniques for EEG-sleep analysis have only recently been applied to a neonatal population. Such studies have been limited to full-term rather than preterm infants and rely on conventional methods that assume stationarity of neurophysiologic signals. We describe a computer system that simultaneously compares behavioral and electrographic components of EEG-sleep in a manner that preserves the integrity of the signals over time, while investigating the time- and frequency-dependent relationships among signals. Strategies for on-line and off-line editing, data storage, and off-line signal processing are described. Computational algorithms regarding analyses of EEG power, motility, and cardiorespiratory data are being used to study the ontogeny of EEG-sleep in asymptomatic preterm and full-term neonates. Computer strategies are based on both principles of stationarity and nonstationarity of physiologic signals and are applied depending on the temporal resolution required for specific signal processing needs.