Methodology and system architecture for automated detection of epileptic seizures in the neonatal EEG
Glover, J.R.; Ktonas, P.Y.; Shastry, M.; Thitai Kumar, A.; Muktevi, V.M.
[Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] EMBS/BMES Conference, 2002. Proceedings of the Second Joint
Volume 1, Issue , 2002 Page(s): 70 - 71 vol.1
Digital Object Identifier   10.1109/IEMBS.2002.1134392
Summary: The automated detection of electrographic seizures in the neonatal EEG is a difficult, unsolved problem because of the variety of seizure patterns and the large number of seizure-like artifacts and non-seizure rhythmic EEG events. In this paper we present an architecture and methodology for such a detection system designed around a combination of signal processing, pattern recognition, heuristic rules, and neural networks. We believe that this hybrid approach offers the best chance for reliable automated detection of neonatal seizures.

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