Show simple item record

AuthorKhlif, M.S.
AuthorMesbah, M.
AuthorBoashash, Boualem
AuthorColditz, P.
Available date2014-04-27T11:57:45Z
Publication Date2010
Publication Name10th International Conference on in Proc. of Information Sciences Signal Processing and their Applications (ISSPA) 2010
CitationM. S. Khlif, M. Mesbah, B. Boashash, and P. Colditz, "Detection of neonatal seizure using multiple filters," in Proc. of Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on, 2010, pp. 284-287
URIhttp://hdl.handle.net/10576/10988
URIhttp://dx.doi.org/10.1109/ISSPA.2010.5605469
AbstractIt is often impossible to accurately differentiate between seizure and non-seizure related activities in irifants based on clinical manifestations alone. The electroencephalogram (EEG) is therefore the best tool available for the recognition, management, and prognosis of neonatal seizures. The EEG signal is known to change structural characteristics between seizure and non-seizure states. In this work, matching pursuit (MP) decomposition. based on a coherent time-frequency (TF) dictionary, has provided us with a measure for quantifYing changes in the structure of the neonatal EEG signal as it alternates between the various states. The quantification of state changes served as the basis for detecting seizures in 35 newborn patients. For each record, a patient-dependent threshold that marks the transition to seizure state is established. The use of multiple filters reduced the amount of artifacts and enhanced the detector performance. Overall, 93.4% detection accuracy and 0.26 false alarms per hour were achieved.
Languageen
PublisherIEEE
SubjectSeizure
EEG
Newborn
Matching pursuit
Time-Frequency
TitleDetection of neonatal seizure using multiple filters
TypeConference Paper
dc.accessType Abstract Only


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record