Real-time segmentation of burst suppression patterns in critical care EEG monitoring

Real-time segmentation of burst suppression patterns in critical care EEG monitoring

Objective Develop a real-time algorithm to automatically discriminate suppressions from non-suppressions (bursts) in electroencephalograms of critically ill adult patients. Methods A real-time method for segmenting adult ICU EEG data into bursts and suppressions is presented based on thresholding lo...

Full description

Bibliographic Details
Main Authors: Shafi, Mouhsin M. (Author), Ching, ShiNung (Contributor), Chemali, Jessica J. (Contributor), Cash, Sydney S. (Author), Brown, Emery N. (Contributor), Westover, M. Brandon (Author), Purdon, Patrick Lee (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences (Contributor), Picower Institute for Learning and Memory (Contributor)
Format: Article
Language:English
Published: Elsevier, 2016-04-15T19:44:29Z.
Subjects:
Article
Online Access:Get fulltext

Internet

Get fulltext

Similar Items