loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: P. J. Cherian 1 ; W. Deburchgraeve 2 ; V. Matic 2 ; M. De Vos 2 ; R. M. Swarte 3 ; J. H. Blok 1 ; P. Govaert 3 ; S. Van Huffel 2 and G. H. Visser 1

Affiliations: 1 University Medical Center Rotterdam, Netherlands ; 2 Katholieke Universiteit Leuven, Belgium ; 3 Sophia Children’s Hospital, Erasmus MC and University Medical Center Rotterdam, Netherlands

ISBN: 978-989-8425-35-5

Keyword(s): Neonatal EEG, Neonatal seizure detection, Epilepsy.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Monitoring and Telemetry ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: We present the improvements made to and subsequent validation of an automated approach to detect neonatal seizures. The evaluation of the algorithm has been performed on a new and extensive data set of neonatal EEGs. Previously, we have classified neonatal seizures visually into two types: the spike train and oscillatory type of seizures and developed two separate algorithms that run in parallel for their automated detection. The first algorithm analyzes the correlation between high-energetic segments of the EEG, whereas the second one detects increases in low-frequency activity (<8 Hz) and then uses an autocorrelation. An improved version of our automated system (called ‘NeoGuard’) uses more informative features for classification and optimized parameters for thresholding. The validation was performed on 756 hours of ‘unseen’ continuous EEG monitoring data from 24 neonates with encephalopathy and recorded seizures. The seizure detection system showed a median sensitivity of 86.9 % pe r patient, positive predictive value (PPV) of 89.5 % and false positive rate of 0.28 per hour. The modified algorithm has a high sensitivity combined with a good PPV whereas false positive rate is much lower compared to the previous version of the algorithm. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.234.214.113

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
J. Cherian, P.; Deburchgraeve, W.; Matic, V.; De Vos, M.; M. Swarte, R.; H. Blok, J.; Govaert, P.; Van Huffel, S. and H. Visser, G. (2011). IMPROVEMENT AND VALIDATION OF AN AUTOMATED NEONATAL SEIZURE DETECTOR.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011) ISBN 978-989-8425-35-5, pages 31-37. DOI: 10.5220/0003127700310037

@conference{biosignals11,
author={P. J. Cherian. and W. Deburchgraeve. and V. Matic. and M. De Vos. and R. M. Swarte. and J. H. Blok. and P. Govaert. and S. Van Huffel. and G. H. Visser.},
title={IMPROVEMENT AND VALIDATION OF AN AUTOMATED NEONATAL SEIZURE DETECTOR},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)},
year={2011},
pages={31-37},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003127700310037},
isbn={978-989-8425-35-5},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)
TI - IMPROVEMENT AND VALIDATION OF AN AUTOMATED NEONATAL SEIZURE DETECTOR
SN - 978-989-8425-35-5
AU - J. Cherian, P.
AU - Deburchgraeve, W.
AU - Matic, V.
AU - De Vos, M.
AU - M. Swarte, R.
AU - H. Blok, J.
AU - Govaert, P.
AU - Van Huffel, S.
AU - H. Visser, G.
PY - 2011
SP - 31
EP - 37
DO - 10.5220/0003127700310037

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.