Title
Epileptic Seizure Prediction Using Diffusion Distance And Bayesian Linear Discriminate Analysis On Intracranial Eeg
Abstract
Epilepsy is a chronic neurological disorder characterized by sudden and apparently unpredictable seizures. A system capable of forecasting the occurrence of seizures is crucial and could open new therapeutic possibilities for human health. This paper addresses an algorithm for seizure prediction using a novel feature - diffusion distance (DD) in intracranial Electroencephalograph (iEEG) recordings. Wavelet decomposition is conducted on segmented electroencephalograph (EEG) epochs and subband signals at scales 3, 4 and 5 are utilized to extract the diffusion distance. The features of all channels composing a feature vector are then fed into a Bayesian Linear Discriminant Analysis (BLDA) classifier. Finally, postprocessing procedure is applied to reduce false prediction alarms. The prediction method is evaluated on the public intracranial EEG dataset, which consists of 577.67 h of intracranial EEG recordings from 21 patients with 87 seizures. We achieved a sensitivity of 85.11% for a seizure occurrence period of 30min and a sensitivity of 93.62% for a seizure occurrence period of 50min, both with the seizure prediction horizon of 10 s. Our false prediction rate was 0.08/h. The proposed method yields a high sensitivity as well as a low false prediction rate, which demonstrates its potential for real-time prediction of seizures.
Year
DOI
Venue
2018
10.1142/S0129065717500435
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
Keywords
Field
DocType
Seizure prediction, intracranial EEG, DWT, diffusion distance, Bayesian linear discriminant analysis
Feature vector,Pattern recognition,Computer science,Neurological disorder,Epilepsy,Epileptic seizure,Artificial intelligence,Linear discriminant analysis,Classifier (linguistics),Electroencephalography,Bayesian probability
Journal
Volume
Issue
ISSN
28
1
0129-0657
Citations 
PageRank 
References 
4
0.40
16
Authors
3
Name
Order
Citations
PageRank
Shasha Yuan1994.73
Weidong Zhou2173.21
Liyan Chen340.40