| dc.contributor.author |
Stevenson, N |
|
| dc.contributor.author |
Mesbah, M |
|
| dc.contributor.author |
Boashash, B |
|
| dc.date.accessioned |
2012-09-21T15:16:06Z |
|
| dc.date.available |
2012-09-21T15:16:06Z |
|
| dc.date.issued |
2007 |
|
| dc.identifier.citation |
Proc. of Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 2007, pp. 7-10. |
en_US |
| dc.identifier.issn |
1557-170X |
|
| dc.identifier.other |
Digital Object Identifier : 10.1109/IEMBS.2007.4352209 |
|
| dc.identifier.uri |
http://hdl.handle.net/10576/10874 |
|
| dc.description |
This paper presents a feature set of four features for use in the detection of seizure in the EEGs of newborns, which are designed with the aid of recent advances in time-frequency modelling of the newborn EEG signal.
(Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (seehttp://www.elsevier.com/locate/isbn/0080443354).
In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). |
en_US |
| dc.description.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 (250background/250 seizure). The covariance of the features is also analysed to indicate the redundancy of thefeature set. The results show significant differences in the features between seizure and background EEG. Thecovariance between the features suggests that there is little redundant information between the features. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
IEEE |
en_US |
| dc.subject |
EEG seizure detection |
en_US |
| dc.subject |
background characteristics |
en_US |
| dc.subject |
covariance function |
en_US |
| dc.subject |
data acquisition |
en_US |
| dc.subject |
electroencephalograms |
en_US |
| dc.subject |
feature extraction |
en_US |
| dc.subject |
newborn EEG |
en_US |
| dc.subject |
seizure characteristics |
en_US |
| dc.subject |
statistical testing |
en_US |
| dc.subject |
MBD |
en_US |
| dc.subject |
modified B distribution |
en_US |
| dc.subject |
time-frequency distributions |
en_US |
| dc.subject |
AM/FM |
en_US |
| dc.subject |
TFD |
en_US |
| dc.subject |
instantaneous frequency |
en_US |
| dc.subject |
correlation |
en_US |
| dc.subject |
Hurst exponent |
en_US |
| dc.title |
A Feature Set for EEG Seizure Detection in the Newborn based on Seizure and Background Charactersitics |
en_US |
| dc.type |
Article |
en_US |