DocumentCode
2375254
Title
Age-independent seizure detection
Author
Faul, Stephen ; Temko, Andriy ; Marnane, William
Author_Institution
Dept. of Electr. Eng., Univ. Coll. Cork, Cork, Ireland
fYear
2009
fDate
3-6 Sept. 2009
Firstpage
6612
Lastpage
6615
Abstract
This paper examines whether an appropriate algorithm, developed for use with neonatal data, could also be used, without alteration, for the detection of seizures in adults with epilepsy. The performance of a feature extraction and SVM classifier system is evaluated on databases of 17 neonatal patients and 15 adult patients. Mean ROC curve areas of 0.96 and 0.94 for neonatal and adult databases respectively show that high accuracy can be achieved independent of age. It is also shown that features contribute differently for neonatal and adult data.
Keywords
electroencephalography; feature extraction; neurophysiology; patient diagnosis; support vector machines; SVM classifier; age independent seizure detection; epilepsy; feature extraction; neonatal data; Adolescent; Adult; Aging; Algorithms; Artifacts; Electroencephalography; Humans; Infant, Newborn; ROC Curve; Seizures; Young Adult;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location
Minneapolis, MN
ISSN
1557-170X
Print_ISBN
978-1-4244-3296-7
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2009.5332553
Filename
5332553
Link To Document