Literature DB >> 29223823

The effect of reducing EEG electrode number on the visual interpretation of the human expert for neonatal seizure detection.

Nathan J Stevenson1, Leena Lauronen2, Sampsa Vanhatalo2.   

Abstract

OBJECTIVES: To measure changes in the visual interpretation of the EEG by the human expert for neonatal seizure detection when reducing the number of recording electrodes.
METHODS: EEGs were recorded from 45 infants admitted to the neonatal intensive care unit (NICU). Three experts annotated seizures in EEG montages derived from 19, 8 and 4 electrodes. Differences between annotations were assessed by comparing intra-montage with inter-montage agreement (K).
RESULTS: Three experts annotated 4464 seizures across all infants and montages. The inter-expert agreement was not significantly altered by the number of electrodes in the montage (p = 0.685, n = 43). Reducing the number of EEG electrodes altered the seizure annotation for all experts. Agreement between the 19-electrode montage (K19,19 = 0.832) was significantly higher than the agreement between 19 and 8-electrode montages (dK = 0.114; p < 0.001, n = 42) or 19 and 4-electrode montages (dK = 0.113, p < 0.001, n = 43). Seizure burden and number were significantly underestimated by the 4 and 8-electrode montage (p < 0.001). No significant difference in agreement was found between 8 and 4-electrode montages (dK = 0.002; p = 0.07, n = 42).
CONCLUSIONS: Reducing the number of EEG electrodes from 19 electrodes resulted in slight but significant changes in seizure detection. SIGNIFICANCE: Four-electrode montages for routine EEG monitoring are comparable to eight electrodes for seizure detection in the NICU.
Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Amplitude integrated EEG; Brain monitoring; Inter-observer agreement; Neonatal EEG; Reliability; Seizure detection

Mesh:

Year:  2017        PMID: 29223823     DOI: 10.1016/j.clinph.2017.10.031

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  6 in total

1.  A dataset of neonatal EEG recordings with seizure annotations.

Authors:  N J Stevenson; K Tapani; L Lauronen; S Vanhatalo
Journal:  Sci Data       Date:  2019-03-05       Impact factor: 6.444

2.  Effects of a reduction of the number of electrodes in the EEG montage on the number of identified seizure patterns.

Authors:  Moritz Tacke; Katharina Janson; Katharina Vill; Florian Heinen; Lucia Gerstl; Karl Reiter; Ingo Borggraefe
Journal:  Sci Rep       Date:  2022-03-17       Impact factor: 4.379

3.  A Review on Machine Learning Approaches in Identification of Pediatric Epilepsy.

Authors:  Mohammed Imran Basheer Ahmed; Shamsah Alotaibi; Sujata Dash; Majed Nabil; Abdullah Omar AlTurki
Journal:  SN Comput Sci       Date:  2022-08-10

4.  A method for AI assisted human interpretation of neonatal EEG.

Authors:  Sergi Gomez-Quintana; Alison O'Shea; Andreea Factor; Emanuel Popovici; Andriy Temko
Journal:  Sci Rep       Date:  2022-06-29       Impact factor: 4.996

5.  Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization.

Authors:  Saeed Montazeri Moghadam; Elana Pinchefsky; Ilse Tse; Viviana Marchi; Jukka Kohonen; Minna Kauppila; Manu Airaksinen; Karoliina Tapani; Päivi Nevalainen; Cecil Hahn; Emily W Y Tam; Nathan J Stevenson; Sampsa Vanhatalo
Journal:  Front Hum Neurosci       Date:  2021-05-31       Impact factor: 3.169

6.  Reliability and accuracy of EEG interpretation for estimating age in preterm infants.

Authors:  Nathan J Stevenson; Maria-Luisa Tataranno; Anna Kaminska; Elena Pavlidis; Robert R Clancy; Elke Griesmaier; James A Roberts; Katrin Klebermass-Schrehof; Sampsa Vanhatalo
Journal:  Ann Clin Transl Neurol       Date:  2020-08-07       Impact factor: 4.511

  6 in total

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