Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model. (5th February 2015)
- Record Type:
- Journal Article
- Title:
- Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model. (5th February 2015)
- Main Title:
- Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model
- Authors:
- Zwanenburg, Alex
Andriessen, Peter
Jellema, Reint K
Niemarkt, Hendrik J
Wolfs, Tim GAM
Kramer, Boris W
Delhaas, Tammo - Abstract:
- Abstract: Seizures below one minute in duration are difficult to assess correctly using seizure detection algorithms. We aimed to improve neonatal detection algorithm performance for short seizures through the use of trend templates for seizure onset and end. Bipolar EEG were recorded within a transiently asphyxiated ovine model at 0.7 gestational age, a common experimental model for studying brain development in humans of 30–34 weeks of gestation. Transient asphyxia led to electrographic seizures within 6–8 h. A total of 3159 seizures, 2386 shorter than one minute, were annotated in 1976 h-long EEG recordings from 17 foetal lambs. To capture EEG characteristics, five features, sensitive to seizures, were calculated and used to derive trend information. Feature values and trend information were used as input for support vector machine classification and subsequently post-processed. Performance metrics, calculated after post-processing, were compared between analyses with and without employing trend information. Detector performance was assessed after five-fold cross-validation conducted ten times with random splits. The use of trend templates for seizure onset and end in a neonatal seizure detection algorithm significantly improves the correct detection of short seizures using two-channel EEG recordings from 54.3% (52.6–56.1) to 59.5% (58.5–59.9) at FDR 2.0 (median (range); p < 0.001, Wilcoxon signed rank test). Using trend templates might therefore aid in detection ofAbstract: Seizures below one minute in duration are difficult to assess correctly using seizure detection algorithms. We aimed to improve neonatal detection algorithm performance for short seizures through the use of trend templates for seizure onset and end. Bipolar EEG were recorded within a transiently asphyxiated ovine model at 0.7 gestational age, a common experimental model for studying brain development in humans of 30–34 weeks of gestation. Transient asphyxia led to electrographic seizures within 6–8 h. A total of 3159 seizures, 2386 shorter than one minute, were annotated in 1976 h-long EEG recordings from 17 foetal lambs. To capture EEG characteristics, five features, sensitive to seizures, were calculated and used to derive trend information. Feature values and trend information were used as input for support vector machine classification and subsequently post-processed. Performance metrics, calculated after post-processing, were compared between analyses with and without employing trend information. Detector performance was assessed after five-fold cross-validation conducted ten times with random splits. The use of trend templates for seizure onset and end in a neonatal seizure detection algorithm significantly improves the correct detection of short seizures using two-channel EEG recordings from 54.3% (52.6–56.1) to 59.5% (58.5–59.9) at FDR 2.0 (median (range); p < 0.001, Wilcoxon signed rank test). Using trend templates might therefore aid in detection of short seizures by EEG monitoring at the NICU. … (more)
- Is Part Of:
- Physiological measurement. Volume 36:Number 3(2015:Mar.)
- Journal:
- Physiological measurement
- Issue:
- Volume 36:Number 3(2015:Mar.)
- Issue Display:
- Volume 36, Issue 3 (2015)
- Year:
- 2015
- Volume:
- 36
- Issue:
- 3
- Issue Sort Value:
- 2015-0036-0003-0000
- Page Start:
- 369
- Page End:
- 384
- Publication Date:
- 2015-02-05
- Subjects:
- neonate -- seizure -- detection -- algorithm -- support vector machine -- EEG -- trend template
Physiology -- Measurement -- Periodicals
Patient monitoring -- Periodicals
612 - Journal URLs:
- http://ioppublishing.org/ ↗
http://iopscience.iop.org/0967-3334 ↗ - DOI:
- 10.1088/0967-3334/36/3/369 ↗
- Languages:
- English
- ISSNs:
- 0967-3334
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
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