A neural-network-based detection of epilepsy

Abstract Diagnosis of epilepsy is primarily based on scalp-recorded electroencephalograms (EEG). Unfortunately the long-term recordings obtained from 'ambulatory recording systems' contain EEG data of up to one week duration, which has introduced new problems for clinical analysis. Traditional methods, where the entire EEG is reviewed by a trained professional, are very time-consuming when applied to recordings of this length. Therefore, several automated diagnostic aid approaches were proposed in recent years, in order to reduce expert effort in analyzing lengthy recordings. The most promising approaches to automated diagnosis are based on neural networks. This paper describes a method for automated detection of epileptic seizures from EEG signals using a multistage nonlinear pre-processing filter in combination with a diagnostic (LAMSTAR) Artificial Neural Network (ANN). Pre-processing via multistage nonlinear filtering, LAMSTAR input preparation, ANN training and system performance (1.6% miss rate, 97.2% overall accuracy when considering both false-alarms and 'misses') are discussed and are shown to compare favorably with earlier approaches presented in recent literature.

[1]  Khashayar Khorasani,et al.  An Adaptive Structure Neural Networks with Application to EEG Automatic Seizure Detection , 1996, Neural Networks.

[2]  Ah Chung Tsoi,et al.  Classification of Electroencephalogram Using Artificial Neural Networks , 1993, NIPS.

[3]  N Pradhan,et al.  Detection of seizure activity in EEG by an artificial neural network: a preliminary study. , 1996, Computers and biomedical research, an international journal.

[4]  N. McGrogan.  Neural network detection of epileptic seizures in the electroencephalogram , 2001 .

[5]  M. Salinsky.  A practical analysis of computer based seizure detection during continuous video-EEG monitoring. , 1997, Electroencephalography and clinical neurophysiology.

[6]  R. Pascual-Marqui.  Review of methods for solving the EEG inverse problem , 1999 .

[7]  J. Gotman.  Automatic recognition of epileptic seizures in the EEG. , 1982, Electroencephalography and clinical neurophysiology.

[8]  T. Babb,et al.  An electronic circuit for detection of EEG seizures recorded with implanted electrodes. , 1974, Electroencephalography and clinical neurophysiology.

[9]  D. Maynard,et al.  An EEG Device for Monitoring Seizure Discharges , 1973, Epilepsia.

[10]  Daniel Graupe,et al.  A Large Memory Storage and Retrieval Neural Network for Adaptive Retrieval and Diagnosis , 1998, Int. J. Softw. Eng. Knowl. Eng..

[11]  K Lehnertz,et al.  Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.