Prediction of epileptic seizures using accumulated energy in a multiresolution framework.
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.
Gigola
S
S
Universidad de Buenos Aires, Buenos Aires, Argentina.
Ortiz
F
F
D'Attellis
C E
CE
Silva
W
W
Kochen
S
S
D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D004566:Electrodes; D004569:Electroencephalography / Q000379:methods*; D004734:Energy Metabolism / Q000502:physiology*; D004827:Epilepsy / Q000145:classification / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D013997:Time Factors