Conference Publication Details
Mandatory Fields
Stevenson, NJ;O'Toole, JM;Korotchikova, I;Boylan, GB
2014 36TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Artefact detection in neonatal EEG
2014
January
Validated
1
WOS: 8 ()
Optional Fields
SEIZURE DETECTION SYSTEM
926
929
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.
Grant Details