EEG waveform analysis using CaseNet

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.<<ETX>>