Abstract

Analysis of the Electroencephalogram (EEG) can assist in developing a deeper understanding of neural development and maturation. Neurologists observed that neonatal EEG patterns change as a function of post conceptional age. Some waveforms such as delta brushes and traće alternant, the discontinuity of background activity, and the percentages of inter hemispheric synchrony are helpful features in using EEG to analyze neural development and maturation. Analyzing these features, however, is based on visual inspection. Quantitative analysis such as spectral EEG and its complexity are extensively studied to better understand the characteristics of EEG. However, the automated synchronization analysis has never been explored. Accordingly, we propose to investigate neurodevelopment in neonates by examining the spatiotemporal patterns of EEG synchronization in the brain. The objectives is to distinguish mid preterm infants from full term infants and also to further classify late preterm infants into either the mid preterm or the full term group using the intensity of the synchronization. The results illustrate that the intensity of synchronization in the mid-preterm and full term babies is different. Moreover, late-preterm babies are statistically categorized in the full term group.