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

Gabriella TamburroKatrien JansenKatrien LemmensAnneleen DereymaekerGunnar NaulaersMaarten De VosSilvia Comani

Published in: PeerJ (2022)

An automated artefact removal method contributes to the pipeline of automated EEG analysis. The proposed algorithm has shown to have good performance and to be effective in neonatal EEG applications.

Keyphrases

resting state
deep learning
machine learning
functional connectivity
working memory
high throughput
loop mediated isothermal amplification
label free
real time pcr
high density
single cell