Neonatal seizure detection algorithms: The effect of channel count

Ana Borovac*, Thomas Philip Runarsson, Gardar Thorvardsson, Steinn Gudmundsson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The number of electrodes used to acquire neonatal EEG signals varies between institutions. Therefore, tools for automatic EEG analysis, such as neonatal seizure detection algorithms, need to be able to handle different electrode montages in order to find widespread use. The aim of this study was to analyse the effect of montage on neonatal seizure detector performance. A full 18-channel montage was compared to reduced 3- and 8-channel montages using a convolutional neural network for seizure detection. Sensitivity decreased by 10 – 18 % for the reduced montages while specificity was mostly unaffected. Electrode artefacts and artefacts associated with biological rhythms caused incorrect classification of non-seizure activity in some cases, but these artefacts were filtered out in the 3-channel montage. Other types of artefacts had little effect. Reduced montages result in some reduction in classifier accuracy, but the performance may still be acceptable. Recording artefacts had a limited effect on detection accuracy.

Original languageEnglish
Pages (from-to)604-607
Number of pages4
JournalCurrent Directions in Biomedical Engineering
Issue number2
Publication statusPublished - 1 Aug 2022

Bibliographical note

Funding Information:
Research funding: The European Union’s Horizon 2020 research and innovation programme under grant agreement No 813483.

Publisher Copyright:
© 2022 The Author(s), published by De Gruyter.

Other keywords

  • neonatal EEG
  • reduced montage
  • Seizure detection


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