Seizure Monitoring and Alert System for Brain Monitoring in an Intensive Care Unit

J. Chris Sackellares (), Deng-Shan Shiau (), Alla R. Kammerdiner and Panos M. Pardalos
Additional contact information
J. Chris Sackellares: Optima Neuroscience, Inc.
Deng-Shan Shiau: Optima Neuroscience, Inc.
Alla R. Kammerdiner: University of Florida
Panos M. Pardalos: University of Florida

Chapter Chapter 20 in Computational Neuroscience, 2010, pp 357-369 from Springer

Abstract: Abstract Although monitoring for most organ systems is commonly used in intensive care units (ICU), brain function monitoring relies almost exclusively upon bedside clinical observations. As a result, a large number of nonconvulsive seizures go undiagnosed every day. Recent clinical studies have demonstrated the clinical utility of continuous EEG monitoring in ICU settings. Continuous EEG is a well-established tool for detecting nonconvulsive seizures, cerebral ischemia, cerebral hypoxia, and other reversible brain disturbances in the ICU. However, the utility of EEG monitoring currently depends on the availability of expert medical professionals, and interpretation is labor intensive. Such experts are available only in tertiary care centers. We have designed a seizure monitoring and alert system (SMAS) that utilizes a seizure susceptibility index (SSI) and seizure detection algorithms based on measures that characterize the spatiotemporal dynamical properties of the EEG signal. The SMAS allows distinguishing the organized seizure patterns from more irregular and less organized background EEG activity. The algorithms and initial results in human long-term EEG recordings are described.

Keywords: Lyapunov Exponent; Epileptic Seizure; Temporal Lobe Epilepsy; Spin Glass; Electrode Site (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-0-387-88630-5_20

Ordering information: This item can be ordered from
http://www.springer.com/9780387886305

DOI: 10.1007/978-0-387-88630-5_20

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().