EEG waveform analysis using CaseNet

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

Research output: Contribution to journalConference articlepeer-review

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
EventImages of the Twenty-First Century - Proceedings of the 11th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 2 - Seattle, WA, USA
Duration: Nov 9 1989Nov 12 1989

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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