| dc.contributor.author |
Boashash, Boualem |
|
| dc.contributor.author |
Zoubir, A.M. |
|
| dc.contributor.author |
Roessgen, M |
|
| dc.date.accessioned |
2011-06-05T07:41:06Z |
|
| dc.date.available |
2011-06-05T07:41:06Z |
|
| dc.date.issued |
1997-07 |
|
| dc.identifier.citation |
13th International Conference on Digital Signal Processing Proceedings, 1997. DSP 97., page(s): 79 - 82 vol.1 |
en_US |
| dc.identifier.isbn |
0-7803-4137-6 |
|
| dc.identifier.other |
Digital Object Identifier: 10.1109/ICDSP.1997.627973 |
|
| dc.identifier.uri |
http://hdl.handle.net/10576/10701 |
|
| dc.description |
This paper presented a solution for the problem of on-line seizure detection from new-born EEG recordings.
A software package that calculates IF estimates and TFDs can be downloaded from the web site: www.time-frequency.net |
en_US |
| dc.description.abstract |
This paper considers the problem of detecting seizures in newborn electroencephalogram (EEG) data. Most current methods for analysing the EEG are based on manual inspection of EEG time-traces, which requires that the data be analysed by a trained electrophysiologist and/or neurologist. This paper introduces an on-line automatic detection scheme. The scheme is based on a model derived from the histology and biophysics of a localised portion of the brain. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
IEEE |
en_US |
| dc.subject |
EEG data |
en_US |
| dc.subject |
EEG time-traces |
en_US |
| dc.subject |
biophysics |
en_US |
| dc.subject |
brain |
en_US |
| dc.subject |
histology |
en_US |
| dc.subject |
localised portion |
en_US |
| dc.subject |
newborn EEG |
en_US |
| dc.subject |
online automatic detection |
en_US |
| dc.subject |
online seizure detection |
en_US |
| dc.subject |
signal processing tools |
en_US |
| dc.subject |
Spike detection |
en_US |
| dc.subject |
seizure characteristics |
en_US |
| dc.title |
On-line detection of seizure in newborn EEG using signal processing tools |
en_US |
| dc.type |
Article |
en_US |