Article

Real-time segmentation and tracking of brain metabolic state in ICU EEG recordings of burst suppression

ABSTRACT

We provide a method for estimating brain metabolic state based on a reduced-order model of EEG burst suppression. The model, derived from previously suggested biophysical mechanisms of burst suppression, describes important electrophysiological features and provides a direct link to cerebral metabolic rate. We design and fit the estimation method from EEG recordings of burst suppression from a neurological intensive care unit and test it on real and synthetic data.

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Available from: M Brandon Westover, Jun 09, 2015
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    • "All EEG data were segmented into a binary sequence of burst and suppression epochs using a previously validated automated suppression detection algorithm [11]. The resulting binary signal was then filtered to produce a continuous measure of burst suppression depth, the BSP ('burst suppression probability'), which quantifies the instantaneous the probability of being in the suppressed state [12]. "
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