A machine learning artefact detection method for single-channel infant event-related potential studies
Simon Marchant,
Marianne van der Vaart,
Kirubin Pillay
et al.
Abstract:Objective
Automated detection of artefact in stimulus-evoked electroencephalographic (EEG) data recorded in neonates will improve the reproducibility and speed of analysis in clinical research compared with manual identification of artefact. Some studies use very short, single-channel epochs of EEG data with little recorded EEG per infant – for example because the clinical vulnerability of the infants limits access for recording. Current artefact-detection methods that perform well on adult data and re… Show more
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