SVM detection of epileptiform activity in routine EEG.

Hdl Handle:
http://hdl.handle.net/10147/200039
Title:
SVM detection of epileptiform activity in routine EEG.
Authors:
Kelleher, Daniel; Temko, Andriy; Nash, Derek; McNamara, Brian; Marnane, William
Affiliation:
Department of Electrical Engineering, University College Cork, Ireland. danielkel@rennes.ucc.ie
Citation:
SVM detection of epileptiform activity in routine EEG. 2010, 2010:6369-72 Conf Proc IEEE Eng Med Biol Soc
Journal:
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Issue Date:
2010
URI:
http://hdl.handle.net/10147/200039
DOI:
10.1109/IEMBS.2010.5627297
PubMed ID:
21096695
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.
Item Type:
Article
Language:
en
Description:
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.
MeSH:
Electroencephalography; Epilepsy; Humans; Signal Processing, Computer-Assisted
ISSN:
1557-170X

Full metadata record

DC FieldValue Language
dc.contributor.authorKelleher, Danielen
dc.contributor.authorTemko, Andriyen
dc.contributor.authorNash, Dereken
dc.contributor.authorMcNamara, Brianen
dc.contributor.authorMarnane, Williamen
dc.date.accessioned2012-01-04T16:01:02Z-
dc.date.available2012-01-04T16:01:02Z-
dc.date.issued2010-
dc.identifier.citationSVM detection of epileptiform activity in routine EEG. 2010, 2010:6369-72 Conf Proc IEEE Eng Med Biol Socen
dc.identifier.issn1557-170X-
dc.identifier.pmid21096695-
dc.identifier.doi10.1109/IEMBS.2010.5627297-
dc.identifier.urihttp://hdl.handle.net/10147/200039-
dc.descriptionRoutine 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.en
dc.description.abstractRoutine 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.-
dc.language.isoenen
dc.subject.meshElectroencephalography-
dc.subject.meshEpilepsy-
dc.subject.meshHumans-
dc.subject.meshSignal Processing, Computer-Assisted-
dc.titleSVM detection of epileptiform activity in routine EEG.en
dc.typeArticleen
dc.contributor.departmentDepartment of Electrical Engineering, University College Cork, Ireland. danielkel@rennes.ucc.ieen
dc.identifier.journalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conferenceen
dc.description.provinceMunster-

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