An automated algorithm to identify and reject artefacts for quantitative EEG analysis during sleep in patients with sleep-disordered breathing

摘要

Large quantities of neurophysiological electroencephalogram (EEG) data are routinely collected in the sleep laboratory. These are underutilised due to the burden of managing artefact contamination. The aim of this study was to develop a new tool for automated artefact rejection that facilitates subsequent quantitative analysis of sleep EEG data collected during routine overnight polysomnography (PSG) in subjects with and without sleep-disordered breathing (SDB).