Prediction of neonatal state and maturational change using dimensional analysis

Nonlinear time series analysis techniques have been used to analyze physiologic signals such as EEG and heart rate. The authors illustrate the application of dimensional analysis (DA) to assess neonatal sleep states at increasing gestational ages up to full-term age. One hundred and sixteen EEG-polygraphic recordings were performed on 55 neonatal subjects between 28 and 43 weeks gestational age from which state assignments were initially scored by visual analysis. A single channel of EEG (i.e., FP1-C3) was selected for dimensional analysis. Two-tailed t-tests were used to test for differences in the correlation dimension (CD) between active and quiet sleep states for both preterm and full-term neonates as a function of maturation. A significant difference in CD between active and quiet sleep states (P<0.001) was noted for the full-term infant. A positive correlation between CD and increasing conceptional age was noted (P<0.001). DA showed an increase in the complexity for both active and quiet sleep as the preterm infant matured toward a full-term corrected age. Lower dimensionality (CD), indicative of reduced complexity, was noted for the healthy preterm cohort at corrected full-term age when compared with the full-term group. Dimensional analysis demonstrated a positive correlation for both active and quiet sleep, as the infant matured toward corrected term age. Lower dimensionality was noted for the healthy preterm cohort at corrected full-term age. These findings support the concept of physiologic dysmaturity for the preterm neonate as a reflection of altered neural plasticity of the brain as a result of the conditions of prematurity.