Abstract
A method for the automatic detection of seizure in newborns is presented. The proposed method is derived from the ability to detect changes in signal structure as the newborn EEG changes from the background state to the seizure state. Matching Pursuit decomposition technique, with an overcomplete time-frequency dictionary, is shown to be an adequate technique for detecting changes in signal structure. Changes are detected by using a new signal measure referred to as structural complexity, which is directly related to the dictionary being used for decomposition. The structural complexity measured is then incorporated in the proposed automatic newborn seizure detection algorithm.
| Original language | English |
|---|---|
| Title of host publication | 2004 12th European Signal Processing Conference, EUSIPCO 2004 |
| Publisher | European Signal Processing Conference, EUSIPCO |
| Pages | 2207-2210 |
| Number of pages | 4 |
| Volume | 06-10-September-2004 |
| ISBN (Electronic) | 9783200001657 |
| Publication status | Published - Apr 3 2015 |
| Event | 12th European Signal Processing Conference, EUSIPCO 2004 - Vienna, Austria Duration: Sep 6 2004 → Sep 10 2004 |
Other
| Other | 12th European Signal Processing Conference, EUSIPCO 2004 |
|---|---|
| Country | Austria |
| City | Vienna |
| Period | 9/6/04 → 9/10/04 |
Fingerprint
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
Cite this
Newborn EEG seizure detection using signal structural complexity. / Rankine, L.; Mesbah, M.; Boashash, B.
2004 12th European Signal Processing Conference, EUSIPCO 2004. Vol. 06-10-September-2004 European Signal Processing Conference, EUSIPCO, 2015. p. 2207-2210 7079745.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Newborn EEG seizure detection using signal structural complexity
AU - Rankine, L.
AU - Mesbah, M.
AU - Boashash, B.
PY - 2015/4/3
Y1 - 2015/4/3
N2 - A method for the automatic detection of seizure in newborns is presented. The proposed method is derived from the ability to detect changes in signal structure as the newborn EEG changes from the background state to the seizure state. Matching Pursuit decomposition technique, with an overcomplete time-frequency dictionary, is shown to be an adequate technique for detecting changes in signal structure. Changes are detected by using a new signal measure referred to as structural complexity, which is directly related to the dictionary being used for decomposition. The structural complexity measured is then incorporated in the proposed automatic newborn seizure detection algorithm.
AB - A method for the automatic detection of seizure in newborns is presented. The proposed method is derived from the ability to detect changes in signal structure as the newborn EEG changes from the background state to the seizure state. Matching Pursuit decomposition technique, with an overcomplete time-frequency dictionary, is shown to be an adequate technique for detecting changes in signal structure. Changes are detected by using a new signal measure referred to as structural complexity, which is directly related to the dictionary being used for decomposition. The structural complexity measured is then incorporated in the proposed automatic newborn seizure detection algorithm.
UR - http://www.scopus.com/inward/record.url?scp=84979877981&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84979877981&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84979877981
VL - 06-10-September-2004
SP - 2207
EP - 2210
BT - 2004 12th European Signal Processing Conference, EUSIPCO 2004
PB - European Signal Processing Conference, EUSIPCO
ER -