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 language | English (US) |
|---|---|
| Pages (from-to) | 2046-2047 |
| Number of pages | 2 |
| Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
| Volume | 11 pt 6 |
| State | Published - Dec 1 1989 |
| Event | Images 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 1989 → Nov 12 1989 |
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics