Literature DB >> 9305283

Evaluation of an automatic seizure detection method for the newborn EEG.

J Gotman1, D Flanagan, B Rosenblatt, A Bye, E M Mizrahi.   

Abstract

In another publication, we described a set of methods for automatic detection of EEG seizures in the newborn. We describe here the evaluation of these methods using a completely new set of data, which were not used in developing the method. This testing data set consisted of recording from 54 patients, lasting an average of 4.4 h. Recordings had 8-16 channels and were obtained, in approximately equal numbers, from 3 institutions in Canada, the USA and Australia. Recording conditions varied from short recordings fully attended by a technologist to overnight recordings largely unattended. The average seizure detection rate was 69% (77%, 53%, 84% in the 3 institutions). False detections occurred at the average rate of 2.3/h (4.1, 1.0, 2.7 in the 3 institutions), with fluctuations that reflected largely the technical quality and level of supervision of the recordings. The results are similar to those obtained in the commonly used method of epilepsy monitoring in adults and allow us to envisage clinical application.

Entities:  

Mesh:

Year:  1997        PMID: 9305283     DOI: 10.1016/s0013-4694(97)00005-2

Source DB:  PubMed          Journal:  Electroencephalogr Clin Neurophysiol        ISSN: 0013-4694


  5 in total

1.  Gaussian mixture models for classification of neonatal seizures using EEG.

Authors:  E M Thomas; A Temko; G Lightbody; W P Marnane; G B Boylan
Journal:  Physiol Meas       Date:  2010-06-28       Impact factor: 2.833

Review 2.  Current Status and Future Directions of Neuromonitoring With Emerging Technologies in Neonatal Care.

Authors:  Gabriel Fernando Todeschi Variane; João Paulo Vasques Camargo; Daniela Pereira Rodrigues; Maurício Magalhães; Marcelo Jenné Mimica
Journal:  Front Pediatr       Date:  2022-03-23       Impact factor: 3.418

3.  Neonatal Seizure Management: Is the Timing of Treatment Critical?

Authors:  Andreea M Pavel; Janet M Rennie; Linda S de Vries; Mats Blennow; Adrienne Foran; Divyen K Shah; Ronit M Pressler; Olga Kapellou; Eugene M Dempsey; Sean R Mathieson; Elena Pavlidis; Lauren C Weeke; Vicki Livingstone; Deirdre M Murray; William P Marnane; Geraldine B Boylan
Journal:  J Pediatr       Date:  2021-10-07       Impact factor: 6.314

4.  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.  Phenobarbital reduces EEG amplitude and propagation of neonatal seizures but does not alter performance of automated seizure detection.

Authors:  Sean R Mathieson; Vicki Livingstone; Evonne Low; Ronit Pressler; Janet M Rennie; Geraldine B Boylan
Journal:  Clin Neurophysiol       Date:  2016-07-25       Impact factor: 3.708

  5 in total

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