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dc.contributor.authorKelleher, Daniel
dc.contributor.authorTemko, Andriy
dc.contributor.authorNash, Derek
dc.contributor.authorMcNamara, Brian
dc.contributor.authorMarnane, William
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
html.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.


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