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Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model
This content has been downloaded from IOPscience. Please scroll down to see the full text. 2015 Physiol. Meas. 36 369 (http://iopscience.iop.org/0967-3334/36/3/369) View the table of contents for this issue, or go to the journal homepage for more
Download details: IP Address: 198.91.37.2 This content was downloaded on 21/02/2015 at 13:50
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Institute of Physics and Engineering in Medicine Physiol. Meas. 36 (2015) 369–384
Physiological Measurement doi:10.1088/0967-3334/36/3/369
Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model Alex Zwanenburg1,2, Peter Andriessen2,3, Reint K Jellema2,3, Hendrik J Niemarkt3, Tim GAM Wolfs2, Boris W Kramer2 and Tammo Delhaas1 1
Department of Biomedical Engineering, Maastricht University, Universiteitssingel 50, Maastricht, The Netherlands 2 Department of Pediatrics, Maastricht University, Maastricht, The Netherlands 3 Department of Pediatrics, Máxima Medical Centre, De Run 4600, Veldhoven, The Netherlands E-mail: [email protected] Received 1 August 2014, revised 11 December 2014 Accepted for publication 5 January 2015 Published 5 February 2015 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
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My IOPscience
Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model
This content has been downloaded from IOPscience. Please scroll down to see the full text. 2015 Physiol. Meas. 36 369 (http://iopscience.iop.org/0967-3334/36/3/369) View the table of contents for this issue, or go to the journal homepage for more
Download details: IP Address: 198.91.37.2 This content was downloaded on 21/02/2015 at 13:50
Please note that terms and conditions apply.
Institute of Physics and Engineering in Medicine Physiol. Meas. 36 (2015) 369–384
Physiological Measurement doi:10.1088/0967-3334/36/3/369
Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model Alex Zwanenburg1,2, Peter Andriessen2,3, Reint K Jellema2,3, Hendrik J Niemarkt3, Tim GAM Wolfs2, Boris W Kramer2 and Tammo Delhaas1 1
Department of Biomedical Engineering, Maastricht University, Universiteitssingel 50, Maastricht, The Netherlands 2 Department of Pediatrics, Maastricht University, Maastricht, The Netherlands 3 Department of Pediatrics, Máxima Medical Centre, De Run 4600, Veldhoven, The Netherlands E-mail: [email protected] Received 1 August 2014, revised 11 December 2014 Accepted for publication 5 January 2015 Published 5 February 2015 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
