Document Detail


Automated artifact removal as preprocessing refines neonatal seizure detection.
MedLine Citation:
PMID:  21705269     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
OBJECTIVE: The description and evaluation of algorithms using Independent Component Analysis (ICA) for automatic removal of ECG, pulsation and respiration artifacts in neonatal EEG before automated seizure detection. METHODS: The developed algorithms decompose the EEG using ICA into its underlying sources. The artifact source was identified using the simultaneously recorded polygraphy signals after preprocessing. The EEG was reconstructed without the corrupting source, leading to a clean EEG. The impact of the artifact removal was measured by comparing the performance of a previously developed seizure detector before and after the artifact removal in 13 selected patients (9 having artifact-contaminated and 4 having artifact-free EEGs). RESULTS: A significant decrease in false alarms (p=0.01) was found while the Good Detection Rate (GDR) for seizures was not altered (p=0.50). CONCLUSIONS: The techniques reduced the number of false positive detections without lowering sensitivity and are beneficial in long term EEG seizure monitoring in the presence of disturbing biological artifacts. SIGNIFICANCE: The proposed algorithms improve neonatal seizure monitoring.
Authors:
M De Vos; W Deburchgraeve; P J Cherian; V Matic; R M Swarte; P Govaert; G H Visser; S Van Huffel
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-6-24
Journal Detail:
Title:  Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology     Volume:  -     ISSN:  1872-8952     ISO Abbreviation:  -     Publication Date:  2011 Jun 
Date Detail:
Created Date:  2011-6-27     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100883319     Medline TA:  Clin Neurophysiol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Affiliation:
Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Leuven-Heverlee, Belgium; Department of Psychology, Neuropsychology Lab., University of Oldenburg, Oldenburg, Germany.
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