Microstructure of longitudinal 24 hour electroencephalograms in healthy preterm infants

BACKGROUND: The aims of the present study were to find electroencephalographic parameters that appropriately represent the microstructure of electroencephalograms (EEG) in different sleep states and to find quantitative criteria for an automatic system of sleep-state classification in preterm infants. METHODS AND RESULTS: Continuous 24 h EEG was performed in 14 normal preterm infants for whom 26 EEG records were obtained. Based on respiratory activity, body movements and rapid eye movements, the different sleep states were determined visually in 30 s epochs. Seven EEG parameters, Minimum Akaike Information Criterion (Min-AIC), total power (TP), component powers (delta, theta, alpha and beta), and the discontinuity were calculated by means of autoregressive and component analyses in 30 s epochs. The student's t test was performed independently for each parameter. Four of the seven parameters (Min-AIC, TP, delta component power and the discontinuity) showed significant differences in different sleep states. The results of multivariate discriminant analysis revealed that the combination of Min-AIC, TP, delta component power and the discontinuity of EEG defined the EEG sleep states well. CONCLUSION: The combination of Min-AIC. TP, delta component power and the discontinuity of EEG defined the EEG sleep states well and might be used to predict sleep state changes in preterm infants of conceptional ages of more than 30 weeks.