Development of an EEG artefact detection algorithm and its application in grading neonatal hypoxic-ischemic encephalopathy

作者：

Highlights：

• Multiple neonatal EEG artefact detection classifiers were designed and compared.

• A convolutional neural network achieved highest artefact detection performance.

• A HIE grade classifier was trained on a multi-centre, 653-hour EEG database.

• A marginal increase in HIE grading performance is shown with artefact detection.

摘要

•Multiple neonatal EEG artefact detection classifiers were designed and compared.•A convolutional neural network achieved highest artefact detection performance.•A HIE grade classifier was trained on a multi-centre, 653-hour EEG database.•A marginal increase in HIE grading performance is shown with artefact detection.

论文关键词：EEG,Convolutional neural network,Artefact detection,Hypoxic-ischemic encephalopathy,Neonatal,Machine learning

论文评审过程：Received 9 March 2022, Revised 10 August 2022, Accepted 24 September 2022, Available online 5 October 2022, Version of Record 21 October 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118917