Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 |
| Pages | 7-10 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 2007 |
| Event | 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France Duration: Aug 23 2007 → Aug 26 2007 |
Other
| Other | 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 |
|---|---|
| Country | France |
| City | Lyon |
| Period | 8/23/07 → 8/26/07 |
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ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics
Cite this
A feature set for EEG seizure detection in the newborn based on seizure and background charactersitics. / Stevenson, N.; Mesbah, M.; Boashash, B.
29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07. 2007. p. 7-10 4352209.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
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.
UR - http://www.scopus.com/inward/record.url?scp=57649176568&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=57649176568&partnerID=8YFLogxK
U2 - 10.1109/IEMBS.2007.4352209
DO - 10.1109/IEMBS.2007.4352209
M3 - Conference contribution
C2 - 18001875
AN - SCOPUS:57649176568
SN - 1424407885
SN - 9781424407880
SP - 7
EP - 10
BT - 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
ER -