Real-time segmentation and tracking of brain metabolic state in ICU EEG recordings of burst suppression
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nihms554064.pdf
Description
Accepted version
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1.64 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Westover, M. Brandon
Ching, ShiNung
Shafi, Mouhsin M.
Cash, Sydney S.
Brown, Emma N.
Date Issued
2015
Journal
Advanced State Space Methods for Neural and Clinical Data
Publisher
Cambridge University Press
Citation
Westover, M. B., et al. “Real-Time Segmentation and Tracking of Brain Metabolic State in ICU EEG Recordings of Burst Suppression.” Advanced State Space Methods for Neural and Clinical Data, edited by Zhe Chen, Cambridge University Press, 2015, 330–44.
Version
Author's final manuscript
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.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Harvard University--MIT Division of Health Sciences and Technology
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1017/CBO9781139941433.015
