Artefact detection in neonatal EEG | IEEE Conference Publication | IEEE Xplore

Artefact detection in neonatal EEG


Abstract:

Artefact detection is an important component of any automated EEG analysis. It is of particular importance in analyses such as sleep state detection and EEG grading where...Show More

Abstract:

Artefact detection is an important component of any automated EEG analysis. It is of particular importance in analyses such as sleep state detection and EEG grading where there is no null state. We propose a general artefact detection system (GADS) based on the analysis of the neonatal EEG. This system aims to detect both major and minor artefacts (a distinction based primarily on amplitude). As a result, a two-stage system was constructed based on 14 features extracted from EEG epochs at multiple time scales: [2, 4, 16, 32]s. These features were combined in a support vector machine (SVM) in order to determine the presence of absence of artefact. The performance of the GADS was estimated using a leave-one-out cross-validation applied to a database of hour long recordings from 51 neonates. The median AUC was 1.00 (IQR: 0.95-1.00) for the detection of major artefacts and 0.89 (IQR: 0.83-0.95) for the detection of minor artefacts.
Date of Conference: 26-30 August 2014
Date Added to IEEE Xplore: 06 November 2014
Electronic ISBN:978-1-4244-7929-0

ISSN Information:

PubMed ID: 25570111
Conference Location: Chicago, IL, USA

References

References is not available for this document.