Title :
Seizure detection by recurrent backpropagation neural network analysis
Author :
Bates, Robyn R. ; Sun, Mingui ; Scheuer, Mark L. ; Sclabassi, Robert J.
Author_Institution :
Dept. of Neurological Surg., Pittsburgh Univ., PA
Abstract :
Detection of the onset of seizure-activity in the EEG record of an epileptic patient is an important step in the localization of seizure foci. We employ the use of three multilayer recurrent neural-network architectures to detect seizure-activity onset in multichannel subdural EEG (SEEG) data. Representing each architecture as (input layer-hidden layer-output layer), the three neural networks examined were 5-10-5, 5-5-1, and 5-10-1
Keywords :
backpropagation; electroencephalography; medical signal processing; neurophysiology; patient diagnosis; recurrent neural nets; EEG record; epileptic patient; multichannel subdural EEG data; multilayer recurrent neural-network architectures; recurrent backpropagation neural network analysis; seizure foci localization; seizure-activity detection; Artificial neural networks; Backpropagation; Biological neural networks; Data analysis; Electroencephalography; Epilepsy; Neural networks; Recurrent neural networks; Signal analysis; Surgery;
Conference_Titel :
Uncertainty Modeling and Analysis, 2003. ISUMA 2003. Fourth International Symposium on
Conference_Location :
College Park, MD
Print_ISBN :
0-7695-1997-0
DOI :
10.1109/ISUMA.2003.1236179
