Title :
Impact of Patient-Specificity on Seizure Onset Detection Performance
Author :
Shoeb, A. ; Bourgeois, B. ; Treves, S.T. ; Schachter, S.C. ; Guttag, J.
Author_Institution :
Massachusetts Inst. of Technol., Cambridge
Abstract :
In this paper we quantify the degree to which patient- specificity affects the detection latency, sensitivity, and specificity of a seizure detector using 536 hours of continuously recorded scalp EEG from 16 epilepsy patients. We demonstrate that a detector that knows of an individual´s seizure and non- seizure EEG outperforms a detector limited to knowledge of an individual´s non-seizure EEG, and a detector limited to knowledge of population seizure and non-seizure EEG.
Keywords :
diseases; electroencephalography; feature extraction; medical signal processing; support vector machines; epilepsy; feature extraction; patient-specificity; scalp EEG; seizure EEG; seizure onset detection performance; support-vector machine classifier; time 536 hour; unary patient-specific detector; Delay; Detectors; Electroencephalography; Epilepsy; Feature extraction; Hospitals; Nervous system; Pediatrics; Scalp; Testing; EEG; Epilepsy; Seizure Detection; Support-Vector Machines; Adolescent; Child; Child, Preschool; Electroencephalography; Female; Humans; Male; Models, Biological; Predictive Value of Tests; Seizures; Signal Processing, Computer-Assisted; Software;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4353240
