CaseNet: a neural network tool for EEG waveform classification
- 7 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
The development of a system to detect online multichannel epileptiform spikes is described. Three main topics are discussed. The first is the preprocessing procedure used on the raw data prior to their presentation to the neural network. Issues reviewed include tradeoffs between preprocessing and system complexity. The second is the development of CaseNet, a neural network development tool used to graphically specify a network architecture from which executable code is generated automatically. Areas discussed include selection of the network architecture, such as choices between supervised and unsupervised learning schemes. The third concerns the interim results of the analysis of single- and four-channel electroencephalogram (EEG) data. The relationship of the spike detection effort to a similar one for seizure detection is also outlined.Keywords
This publication has 5 references indexed in Scilit:
- Neural Networks and Natural IntelligencePublished by MIT Press ,1988
- Self-Organization and Associative MemoryPublished by Springer Nature ,1988
- Medical diagnostic expert system based on PDP modelPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1988
- Parallel free-text search on the connection machine systemCommunications of the ACM, 1986
- Parallel Distributed ProcessingPublished by MIT Press ,1986