title: Early Seizure Detection Algorithm Based on Intracranial EEG and Random Forest Classification.
abstract: The goal of this study is to provide a seizure detection algorithm that is relatively simple to implement on a microcontroller, so it can be used for an implantable closed loop stimulation device. We propose a set of 11 simple time domain and power bands features, computed from one intracranial EEG contact located in the seizure onset zone. The classification of the features is performed using a random forest classifier. Depending on the training datasets and the optimization preferences, the performance of the algorithm were: 93.84% mean sensitivity (100% median sensitivity), 3.03 s mean (1.75 s median) detection delays and 0.33/h mean (0.07/h median) false detections per hour.
authors.affiliation: Epilepsy Center, University Hospital of Freiburg, Freiburg, Germany.|Excellence Cluster BrainLinks-Brain Tools, University of Freiburg, Germany.
authors.forename: Cristian
authors.initials: C
authors.lastname: Donos
authors.affiliation: Epilepsy Center, University Hospital of Freiburg, Freiburg, Germany.|Excellence Cluster BrainLinks-Brain Tools, University of Freiburg, Germany.
authors.forename: Matthias
authors.initials: M
authors.lastname: Dümpelmann
authors.affiliation: Epilepsy Center, University Hospital of Freiburg, Freiburg, Germany.|Excellence Cluster BrainLinks-Brain Tools, University of Freiburg, Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Schulze-Bonhage
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001921:Brain / Q000503:physiopathology* / Q000601:surgery; D042241:Early Diagnosis; D000069280:Electrocorticography / Q000379:methods*; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D058542:Implantable Neurostimulators; D008297:Male; D008875:Middle Aged; D012640:Seizures / Q000175:diagnosis* / Q000503:physiopathology* / Q000601:surgery; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D055815:Young Adult
keywords: EEG features; Epilepsy; feature classification; intracranial EEG; seizure detection