Title
Automated Detection and Removal of Cardiac and Pulse Interferences from Neonatal EEG Signals
Abstract
Electrical cardiac and pulsatile interference is very difficult to remove from electroencephalographic (EEG) signals, especially if recorded in neonates, for which a small number of EEG channels is used. Several methods were proposed, including Blind Source Separation (BSS) methods that required the use of artificial cardiac-related signals to improve the separation of artefactual components. To optimize the separation of cardiac-related artefactual components, we propose a method based on Independent Component Analysis (ICA) that exploits specific features of the real electrocardiographic (ECG) signals that were simultaneously recorded with the neonatal EEG. A total of forty EEG segments from 19-channel neonatal EEG recordings with and without seizures were used to test and validate the performance of our method. We observed a significant reduction in the number of independent components (ICs) containing cardiac-related interferences, with a consequent improvement in the automated classification of the separated ICs. The comparison with the expert labeling of the ICs separately containing electrical cardiac and pulsatile interference led to an accuracy = 0.99, a false omission rate = 0.01 and a sensitivity = 0.93, outperforming existing methods. Furthermore, we verified that true brain activity was preserved in neonatal EEG signals reconstructed after the removal of artefactual ICs, demonstrating the effectiveness of our method and its safe applicability in a clinical context.
Year
DOI
Venue
2021
10.3390/s21196364
SENSORS
Keywords
DocType
Volume
neonatal electroencephalography (EEG), automated artefact removal, independent component analysis (ICA), blind source separation methods (BSS), cardiac interference, pulse interference, electrocardiography (ECG)
Journal
21
Issue
ISSN
Citations 
19
1424-8220
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Gabriella Tamburro100.68
Pierpaolo Croce200.34
Filippo Zappasodi35310.43
Silvia Comani41168.78