Name
Title | ||
|---|---|---|
Recurrent neural network based prediction of epileptic seizures in intra- and extracranial EEG |
Abstract | ||
|---|---|---|
Predicting the onset of epileptic seizure is an important and difficult biomedical problem, which has attracted substantial attention of the intelligent computing community over the past two decades. We apply recurrent neural networks (RNN) combined with signal wavelet decomposition to the problem. We input raw EEG and its wavelet-decomposed subbands into RNN training/testing, as opposed to specific signal features extracted from EEG. To the best of our knowledge this approach has never been attempted before. The data used included both scalp and intracranial EEG recordings obtained from two epileptic patients. We demonstrate that the existence of a “preictal” stage (immediately preceding seizure) of some minutes duration is quite feasible. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1016/S0925-2312(99)00126-5 | Neurocomputing |
Keywords | Field | DocType |
EEG,Epileptic seizure,Recurrent neural network,Wavelet transform | Wavelet decomposition,Pattern recognition,Intelligent computing,Recurrent neural network,Speech recognition,Epileptic seizure,Artificial intelligence,Scalp,Mathematics,Electroencephalography,Machine learning,Wavelet transform | Journal |
Volume | Issue | ISSN |
30 | 1-4 | 0925-2312 |
Citations | PageRank | References |
62 | 13.24 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arthur Petrosian | 1 | 62 | 13.91 |
| Danil V. Prokhorov | 2 | 293 | 26.22 |
| Richard Homan | 3 | 62 | 13.24 |
| Richard Dasheiff | 4 | 62 | 13.24 |
| Donald Wunsch | 5 | 96 | 17.68 |