DocumentCode :
2941676
Title :
SVM detection of epileptiform activity in routine EEG
Author :
Kelleher, Daniel ; Temko, Andriy ; Nash, Derek ; McNamara, Brian ; Marnane, William
Author_Institution :
Dept. of Electr. Eng., Univ. Coll. Cork, Cork, Ireland
fYear :
2010
fDate :
Aug. 31 2010-Sept. 4 2010
Firstpage :
6369
Lastpage :
6372
Abstract :
Routine electroencephalogram (EEG) is an important test in aiding the diagnosis of patients with suspected epilepsy. These recordings typically last 20-40 minutes, during which signs of abnormal activity (spikes, sharp waves) are looked for in the EEG trace. It is essential that events of short duration are detected during the routine EEG test. The work presented in this paper examines the effect of changing a range of input values to the detection system on its ability to distinguish between normal and abnormal EEG activity. It is shown that the length of analysis window in the range of 0.5s to 1s are well suited to the task. Additionally, it is reported that patient specific systems should be used where possible due to their better performance.
Keywords :
electroencephalography; medical disorders; medical signal processing; neurophysiology; patient diagnosis; signal detection; support vector machines; SVM detection; abnormal activity; analysis window length; electroencephalogram; epilepsy; epileptiform activity; patient diagnosis; routine EEG; sharp waves; spikes; Brain modeling; Electroencephalography; Feature extraction; Pediatrics; Sensitivity; Time frequency analysis; Training; Electroencephalography; Epilepsy; Humans; Signal Processing, Computer-Assisted;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4123-5
Type :
conf
DOI :
10.1109/IEMBS.2010.5627297
Filename :
5627297
Link To Document :
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