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