Computer classification of sleep in preterm and full-term neonates at similar postconceptional term ages.
A classification strategy of neonatal sleep is being developed by comparing visually scored minutes of 21 channels of electroencephalographic (EEG)/polygraphic recordings with the corresponding values for each physiological signal derived from either visual or computer analyses. Continuous 3-hour sleep studies on 54 preterm and full-term neonates at similar postconceptional term ages were acquired under environmentally controlled conditions using a computerized monitoring system. An on-line event marker program recorded behavioral observations. One of three EEG sleep states was assigned to each of 8,995 minutes by traditional visual analysis criteria. EEG spectral values, spectral and nonspectral cardiorespiratory calculations and behaviorally observed movements, arousals and rapid eye movement counts were submitted for discriminant analysis. Based on the total minutes known for each of three states (i.e. active, quiet and awake), linear combinations of all specified digitized parameters were formed into an arithmetic algorithm by use of discriminant analysis, which served as the basis of a state assignment for each minute. Fifty percent of the data were arbitrarily used as the training set to derive the state classification model. The remaining fifty percent of the data were used as the cross-validation "test sample" to determine the accuracy of the classification when compared to the visually analyzed score for each corresponding minute. Thirteen out of 32 physiological measures best predicted state of both preterm and full-term neonatal groups. For both groups, the correct classification for active sleep was 90.3%, quiet sleep was 97.4%, awake was 97% and the overall accuracy was 93.3%. However, the order of significance for specific variables differed between these two neonatal groups. Differences in the order of variables that predict sleep states between preterm and full-term infants may reflect adaptation of brain function of the preterm infant to prematurity and/or prolonged extrauterine experience.
Scher
M S
MS
Department of Pediatrics, Magee-Womens Hospital, Pittsburgh, Pennsylvania 15213, USA.
Dokianakis
S G
SG
Sun
M
M
Steppe
D A
DA
Guthrie
R D
RD
Sclabassi
R J
RJ
D002675:Child, Preschool; D004569:Electroencephalography; D001330:Electronic Data Processing; D006339:Heart Rate; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007234:Infant, Premature; D012119:Respiration; D012895:Sleep, REM; D014851:Wakefulness