Automated detection and removal of flat line segments and large amplitude fluctuations in neonatal electroencephalography.

ABSTRACT:

Background

Artefact removal in neonatal electroencephalography (EEG) by visual inspection generally depends on the expertise of the operator, is time consuming and is not a consistent pre-processing step to the pipeline for the automated EEG analysis. Therefore, there is the need for the automated detection and removal of artefacts in neonatal EEG, especially of distinct and predominant artefacts such as flat line segments (mainly caused by instrumental error where contact between electrodes and head box is lost) and large amplitude fluctuations (related to neonatal movements).

Method

A threshold-based algorithm for the automated detection and removal of flat line segments and large amplitude fluctuations in neonatal EEG of infants at term-equivalent age is developed. The al

SUBMITTER: Tamburro G 

PROVIDER: S-EPMC9285485 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature