Automatic newborn EEG seizure spike and event detection using adaptive window optimization

L. Rankine, M. Mesbah, B. Boashash

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Paroxysmal events such as spikes in the newborn EEG are key indicators of central nervous system (CNS) functioning. Newborn EEG seizure events, which are characterised by repetitive spiking events, correspond to CNS dysfunction. Detection and identification of seizure is crucial so that steps can be taken to alleviate the factors causing seizure and to reduce the risk of brain damage. This paper provides a new EEG spike detection method based on an adaptive window optimization algorithm which has been used for an adaptive spectrogram. This technique is assessed using synthetic and real signals containing spikes. The spike detection method is then incorporated into an automatic newborn EEG seizure detection algorithm, which is evaluated using EEG recordings from 8 neonates.

Original languageEnglish
Title of host publicationProceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005
Pages187-190
Number of pages4
Volume1
DOIs
Publication statusPublished - 2005
Event8th International Symposium on Signal Processing and its Applications, ISSPA 2005 - Sydney, Australia
Duration: Aug 28 2005Aug 31 2005

Other

Other8th International Symposium on Signal Processing and its Applications, ISSPA 2005
CountryAustralia
CitySydney
Period8/28/058/31/05

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Rankine, L., Mesbah, M., & Boashash, B. (2005). Automatic newborn EEG seizure spike and event detection using adaptive window optimization. In Proceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005 (Vol. 1, pp. 187-190). [1580227] https://doi.org/10.1109/ISSPA.2005.1580227