title: Towards real-time in-implant epileptic seizure prediction.
abstract: We present an architecture of an epileptic seizure prediction system suitable for an implantable implementation. The microsystem comprises a neural interface, a spectral analysis processor and an artificial neural network (ANN). The neural interface and the spectral analysis processor have been prototyped in a 0.35 microm CMOS technology with experimental results are presented. The wavelet-based artificial neural network predicts the onsets of seizure up to two minutes before their occurrence in an in-vitro epilepsy model using a mouse hippocampal brain slice with recurrent spontaneous seizures.
authors.affiliation: Department of Electrical & Computer Engineering, University of Toronto, ON, Canada.
authors.forename: Joseph N Y
authors.initials: JN
authors.lastname: Aziz
authors.forename: Rafal
authors.initials: R
authors.lastname: Karakiewicz
authors.forename: Roman
authors.initials: R
authors.lastname: Genov
authors.forename: Berj L
authors.initials: BL
authors.lastname: Bardakjian
authors.forename: Miron
authors.initials: M
authors.lastname: Derchansky
authors.forename: Peter L
authors.initials: PL
authors.lastname: Carlen
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted; D004567:Electrodes, Implanted; D004569:Electroencephalography / Q000295:instrumentation / Q000379:methods; D004827:Epilepsy / Q000175:diagnosis*; D006801:Humans; D051379:Mice; D008838:Microcomputers; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors