SEMINARS
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Spring 2009
STATISTICS
COLLOQUIUM
Friday, March 27, 2009
3:30-4:00—Refreshments
4:00-5:00—Talk
Yost Hall, Room 101
Alexandra Piryatinska, Ph.D.
Assistant Professor,
Department of Mathematics, San Francisco State University
Multivariate Analysis of EEG-Sleep Patterns of Neonates
We analyzed EEG-sleep patterns of the neonates. The level of brain dysmaturity of a neonate is difficult to assess by direct physical or cognitive examination, but dysmaturity is known to be directly related to the structure of neonatal sleep as reflected in the nonstationary time series produced by EEG signals which, importantly, can be collected trough a noninvasive procedure. In the past, the assessmentof sleep EEG structure has often been done manually by an experienced clinician. We developed an algorithm for sleep stage separation using multichannel EEG signal. We separated different sleep stages corresponding to different stationary segments of the EEG signal based on statistical analysis of the spectral and nonlinear characteristics of the sleep EEG recordings. We found the channels and characteristics which are most suitable to separate a sleep stages.
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