Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization

Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization

Neonatal brain monitoring in the neonatal intensive care units (NICU) requires a continuous review of the spontaneous cortical activity, i.e., the electroencephalograph (EEG) background activity. This needs development of bedside methods for an automated assessment of the EEG background activity. In...

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Bibliographic Details
Main Authors: Saeed Montazeri Moghadam, Elana Pinchefsky, Ilse Tse, Viviana Marchi, Jukka Kohonen, Minna Kauppila, Manu Airaksinen, Karoliina Tapani, Päivi Nevalainen, Cecil Hahn, Emily W. Y. Tam, Nathan J. Stevenson, Sampsa Vanhatalo
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-05-01
Series:Frontiers in Human Neuroscience
Subjects:
neonatal EEG
EEG monitoring
neonatal intensive care unit
background classifier
support vector machine
artificial neural network
Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2021.675154/full

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https://www.frontiersin.org/articles/10.3389/fnhum.2021.675154/full

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