Automatic Detection of Interictal Spikes using Data Mining Models

VALENTI P., CAZAMAJOU E., SCARPETTINI M., AIZEMBERG A., SILVA W., KOCHEN S.

JOURNAL OF NEUROSCIENCE METHODS

Elsevier

Año: 2006 vol. 150 p. 105 - 110

0165-0270

Records of brain electrical activity from intracranial EEG of four patients with different types of epilepsy are analyzed to predict the epileptic seizure onset. A method based on the evolution of the accumulated energy using wavelet analysis is introduced. This is an efficient method to predict epileptic seizures: from 13 preseizure signals, the seizure onset in 12 of those are predicted.