ESTIMATING OF BRAIN DEVELOPMENT IN NEWBORNS BY FRACTAL ANALYSIS OF SLEEP ELECTROENCEPHALOGRAPHIC (EEG) SIGNAL

Analysis of the brain development is one of the major research areas in human neuroscience. In order to analyze the human brain development, scientists employ different brain imaging techniques. One of the typical techniques to measure the brain activity is electroencephalography (EEG). In this paper, we do complexity analysis on the EEG signal recorded from the newborns during their sleep, in different weeks of post conception. We analyze how the nonlinear structure of EEG signal changes for newborns with their ages by using fractal theory. The result of our analysis showed that the EEG signals for newborn in 45 weeks have the highest fractal dimension. The lowest fractal dimension of EEG signal was obtained for newborns in 36 weeks. Based on our analysis, we conclude that the complexity of brain signal significantly changes with the newborn age. The proposed method is not limited to the analysis of the brain development, and can be applied to investigate the brain activity in different tasks.