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Activity Number:
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154
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #309849 |
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Title:
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Statistical Analysis of EEG-Sleep Patterns of Neonates
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Author(s):
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Alexandra Piryatinska*+
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Companies:
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San Francisco State University
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Address:
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1000 Continentals way apt 214, Belmont, CA, 94002,
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Keywords:
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time series analysis ; change point detection ; cluster analysis ; analysis of eeg
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Abstract:
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We analyze the EEG-sleep signal of neonates. A rigorous methodology to analyze EEG-sleep pattern are needed to assess functional brain maturation of infants. Changes in ultradian rhythm of the sleep (change between sleep stages) is one of the important characteristics related the brain maturation. We consider the EEG signal as a piecewise stationary time series. Several EEG spectral and nonlinear dynamics characteristics are being estimated. We find the characteristics that are significantly different for the different sleep stages. The nonparametric change-point detection algorithm and cluster analysis is applied to these characteristics to obtain the sleep stage separation. The groups of pre-term and full-term neonates have been compared.
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