TY - GEN
T1 - A feature set for EEG seizure detection in the newborn based on seizure and background charactersitics
AU - Stevenson, N.
AU - Mesbah, M.
AU - Boashash, B.
PY - 2007
Y1 - 2007
N2 - This paper presents a set of four features to be used in the detection of seizure in the electroencephalograms (EEGs) of newborns. The features are designed with the aid of recent advances in modelling of the newborn EEG. The performance of the features is analysed with a database of 500 epochs of newborn EEG (250 background/250 seizure). The covariance of the features is also analysed to indicate the redundancy of the feature set. The results show significant differences in the features between seizure and background EEG. The covariance between the features suggests that there is little redundant information between the features.
AB - This paper presents a set of four features to be used in the detection of seizure in the electroencephalograms (EEGs) of newborns. The features are designed with the aid of recent advances in modelling of the newborn EEG. The performance of the features is analysed with a database of 500 epochs of newborn EEG (250 background/250 seizure). The covariance of the features is also analysed to indicate the redundancy of the feature set. The results show significant differences in the features between seizure and background EEG. The covariance between the features suggests that there is little redundant information between the features.
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U2 - 10.1109/IEMBS.2007.4352209
DO - 10.1109/IEMBS.2007.4352209
M3 - Conference contribution
C2 - 18001875
AN - SCOPUS:57649176568
SN - 1424407885
SN - 9781424407880
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 7
EP - 10
BT - 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
T2 - 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Y2 - 23 August 2007 through 26 August 2007
ER -