EEG waveform analysis using CaseNet

R. C. Eberhart, R. W. Dobbins, William Webber

Research output: Contribution to journalArticle

Abstract

CaseNet, a neural-network-based tool for the analysis and classification of EEG waveforms, is described. The development of CaseNet, and of the EEG signal preprocessing procedures required to use CaseNet for multichannel epileptiform spike detection are reviewed. Results using CaseNet to detect epileptiform spikes in a four-channel offline system are presented. The spike detection work described is part of a larger cooperative program. Program goals include online spike detection and online seizure prediction and detection.

Original languageEnglish (US)
Pages (from-to)2046-2047
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume11 pt 6
StatePublished - Dec 1 1989

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Waveform analysis
Electroencephalography
Seizures
Neural networks

ASJC Scopus subject areas

  • Bioengineering
  • Engineering(all)

Cite this

EEG waveform analysis using CaseNet. / Eberhart, R. C.; Dobbins, R. W.; Webber, William.

In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 11 pt 6, 01.12.1989, p. 2046-2047.

Research output: Contribution to journalArticle

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