title: Evaluation of a computerized system for recognition of epileptic activity during long-term EEG recording.
abstract: A new method of recognition of epileptic activity using adaptive segmentation in EEG during long-term intensive monitoring was developed in Tampere. The performance of the system was validated and compared to the commercially available discharge recognition system of Gotman. Twelve approximately 30 min EEG segments recorded during intensive monitoring from 6 patients were analysed. On these EEG segments two EEG specialists marked the occurrence of epileptic activity independently. Later they re-evaluated any differences in their scoring. This consensus file was used as a reference in validating the performance of the two computer programs. We found that the program developed in Tampere detected discharge activity more often than the Gotman system. Both systems performed poorly in spike recognition. In the specificity of the recognized segments, the Gotman system was better.
authors.affiliation: University of Tampere, Department of Neurology, Finland.
authors.forename: T
authors.initials: T
authors.lastname: Pietilä
authors.forename: S
authors.initials: S
authors.lastname: Vapaakoski
authors.forename: U
authors.initials: U
authors.lastname: Nousiainen
authors.forename: A
authors.initials: A
authors.lastname: Värri
authors.forename: H
authors.initials: H
authors.lastname: Frey
authors.forename: V
authors.initials: V
authors.lastname: Häkkinen
authors.forename: Y
authors.initials: Y
authors.lastname: Neuvo
mesh_terms: D003199:Computer Systems; D004569:Electroencephalography / Q000295:instrumentation*; D004827:Epilepsy / Q000503:physiopathology*; D006801:Humans; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013997:Time Factors