%0 Journal Article %1 FGE:OPE:06 %A Firpi, Hiram %A Goodman, Erik %A Echauz, Javier %D 2006 %J Annals of Biomedical Engineering %K Artificial Epilepsy, Feature Seizure State-space algorithms, extraction, feature, genetic prediction, programming, reconstruction %N 3 %P 515--529 %R doi:10.1007/s10439-005-9039-7 %T On Prediction of Epileptic Seizures by Means of Genetic Programming Artificial Features %V 34 %X A general-purpose, systematic algorithm is presented, consisting of a genetic programming module and a k-nearest neighbour classifier to automatically create artificial features computer-crafted features possibly without a known physical meaning directly from the reconstructed state-space trajectory of intracranial EEG signals that reveal predictive patterns of epileptic seizures. The algorithm was evaluated with IEEG data from seven patients, with prediction defined over a horizon of 1-5 min before unequivocal electrographic onset. A total of 59 baseline epochs (nonseizures) and 55 preictal epochs (preseizures) were used for validation purposes. Among the results, it is shown that 12 seizures out of 55 were missed while four baseline epochs were misclassified, yielding 79per cent sensitivity and 93per cent specificity.

@article{FGE:OPE:06, abstract = {A general-purpose, systematic algorithm is presented, consisting of a genetic programming module and a k-nearest neighbour classifier to automatically create artificial features computer-crafted features possibly without a known physical meaning directly from the reconstructed state-space trajectory of intracranial EEG signals that reveal predictive patterns of epileptic seizures. The algorithm was evaluated with IEEG data from seven patients, with prediction defined over a horizon of 1-5 min before unequivocal electrographic onset. A total of 59 baseline epochs (nonseizures) and 55 preictal epochs (preseizures) were used for validation purposes. Among the results, it is shown that 12 seizures out of 55 were missed while four baseline epochs were misclassified, yielding 79per cent sensitivity and 93per cent specificity.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Firpi, Hiram and Goodman, Erik and Echauz, Javier}, biburl = {https://www.bibsonomy.org/bibtex/2c630abe32f18412e74d5ac9b27954b9e/brazovayeye}, doi = {doi:10.1007/s10439-005-9039-7}, interhash = {74b9f95ad9175e2dc20b8d90d966dec1}, intrahash = {c630abe32f18412e74d5ac9b27954b9e}, journal = {Annals of Biomedical Engineering}, keywords = {Artificial Epilepsy, Feature Seizure State-space algorithms, extraction, feature, genetic prediction, programming, reconstruction}, month = {March}, number = 3, pages = {515--529}, timestamp = {2008-06-19T17:39:38.000+0200}, title = {On Prediction of Epileptic Seizures by Means of Genetic Programming Artificial Features}, volume = 34, year = 2006 }