Literature DB >> 15627940

Neonatal seizure monitoring using non-linear EEG analysis.

L S Smit1, R J Vermeulen, W P F Fetter, R L M Strijers, C J Stam.   

Abstract

Birth asphyxia is a major concern in neonatal care. Epileptic seizures are associated with subsequent neurodevelopmental deficits. Eighty-five percent of these seizures remain subclinical and therefore an on-line monitoring device is needed. In an earlier study we showed that the synchronization likelihood was able to distinguish between neonatal EEG epochs with and without epileptic seizures. In this study we investigated whether the synchronization likelihood can be used in complete EEGs, without artifact removal. Twenty complete EEGs from 20 neonatal patients were studied. The synchronization likelihood was calculated and correlated with the visual scoring done by 3 experts. In addition, we determined the influence of seizure length on the likelihood of detection. Using the raw unfiltered EEG data we found a sensitivity of 65.9 % and a specificity of 89.8 % for the detection of seizure activity in each epoch. In addition, the seizure detection rate was 100 % when the seizures lasted for 100 seconds or more. The synchronization likelihood seems to be a useful tool in the automatic monitoring of epileptic seizures in infants on the neonatal ward. Due to the retrospective nature of our study, the consequences for clinical intervention cannot yet be determined and prospective studies are needed. Therefore, we will conduct a prospective study on the neonatal intensive care unit with a recently developed on-line version of the synchronization likelihood analysis.

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Year:  2004        PMID: 15627940     DOI: 10.1055/s-2004-830367

Source DB:  PubMed          Journal:  Neuropediatrics        ISSN: 0174-304X            Impact factor:   1.947


  5 in total

1.  Seizure detection in adult ICU patients based on changes in EEG synchronization likelihood.

Authors:  A J C Slooter; E M Vriens; F S S Leijten; J J Spijkstra; A R J Girbes; A C van Huffelen; C J Stam
Journal:  Neurocrit Care       Date:  2006       Impact factor: 3.210

2.  Clinical implementation of a neonatal seizure detection algorithm.

Authors:  Andriy Temko; William Marnane; Geraldine Boylan; Gordon Lightbody
Journal:  Decis Support Syst       Date:  2015-02       Impact factor: 5.795

3.  Applications of advanced signal processing and machine learning in the neonatal hypoxic-ischemic electroencephalogram.

Authors:  Hamid Abbasi; Charles P Unsworth
Journal:  Neural Regen Res       Date:  2020-02       Impact factor: 5.135

4.  Interobserver agreement for neonatal seizure detection using multichannel EEG.

Authors:  Nathan J Stevenson; Robert R Clancy; Sampsa Vanhatalo; Ingmar Rosén; Janet M Rennie; Geraldine B Boylan
Journal:  Ann Clin Transl Neurol       Date:  2015-10-01       Impact factor: 4.511

5.  Validation of an automated seizure detection algorithm for term neonates.

Authors:  Sean R Mathieson; Nathan J Stevenson; Evonne Low; William P Marnane; Janet M Rennie; Andrey Temko; Gordon Lightbody; Geraldine B Boylan
Journal:  Clin Neurophysiol       Date:  2015-05-09       Impact factor: 3.708

  5 in total

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