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Seizure detection using digital trend analysis: Factors affecting utility by Cigdem I. Akman; Vesna Micic; Anita Thompson; James J. Riviello Jr. is a Medicine article available to read on EtoBox.

What is Seizure detection using digital trend analysis: Factors affecting utility about?

Background: EEG monitoring is important for the early detection of seizures during the course of critical illness. However, the logistics of real time EEG interpretation is challenging for the neurophysiology and critical care medicine teams. This study evaluated factors affecting the utility of digital trend analysis (DTA) for rapid seizure identification in children. Methods: Digital EEG files of seizures in critically ill children were retrieved for DTA. The envelop trend (ET) and compressed spectral array (CSA) were applied to the raw EEG data and presented to an experienced and inexperienced user for interpretation who were blinded to conventional EEG findings. The EEG findings with and without presence of seizures and features of seizures were analyzed. Results: We found that a number of factors affected accurate seizure detection including factors related to interpreter's experiences, display size and type of DTA methods used for analysis in addition to baseline EEG findings. ET was more dependent on user experience, furthermore, display size and multimodal DTA application (CSA and ET combined) increased the sensitivity of seizure detection for the experienced user compared

Who reads Seizure detection using digital trend analysis: Factors affecting utility?

Author

Cigdem I. Akman; Vesna Micic; Anita Thompson; James J. Riviello Jr.

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0920-1211)

Published

2011

Language

EN

Field

Medicine (Health Sciences)