Real-Time Segmentation of Burst Suppression Patterns in Critical Care EEG Monitoring

This dataset is intended to allow reproducibility of the results reported in
the following manuscript: "Real-time segmentation of burst suppression
patterns in critical care EEG monitoring. J Neurosci Methods. 2013 Sep
30;219(1):131-41".

Brief abstract: Automatic computational analysis of burst suppression
patterns in neurological critically ill patients can provide important
clinical information regarding brain state, for example during recovery from
hypoxic ischemic encephalopathy and for guiding medical treatment of
refractory status epilepticus with pharmacologically induced coma. A robust
method is presented for automated segmentation of adult burst suppression ICU
EEG patterns, and is validated against 20 manual EEG segmentations
encompassing a wide range of different burst suppression depths and patterns.
Expert-level automated real-time segmentation of burst suppression EEG data is
demonstrated.