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.
Scher
M S
MS
Developmental Neurophysiology Laboratory, Magee-Women's Hospital, Pittsburgh, PA 15210.
Sun
M
M
Hatzilabrou
G M
GM
Greenberg
N L
NL
Cebulka
G
G
Krieger
D
D
Guthrie
R D
RD
Sclabassi
R J
RJ
D003199:Computer Systems; D004569:Electroencephalography / Q000295:instrumentation*; D005071:Evoked Potentials / Q000502:physiology; D006801:Humans; D007231:Infant, Newborn / Q000502:physiology*; D008122:Local Area Networks; D008905:Minicomputers; D012815:Signal Processing, Computer-Assisted; D012894:Sleep Stages / Q000502:physiology*; D012984:Software