DocumentCode
3075028
Title
Contrasting spatial, temporal and Spatio-Temporal ICA applied to ictal EEG recordings
Author
James, Christopher J. ; Davies, Mike E.
Author_Institution
Signal Processing and Control Group, ISVR, University of Southampton, SO17 1BJ, UK
fYear
2008
fDate
20-25 Aug. 2008
Firstpage
3336
Lastpage
3339
Abstract
In this paper we contrast three implementations of Independent Component Analysis (ICA) as applied to epileptic scalp electroencephalographic (EEG) recordings, these are; Spatial (Ensemble) ICA, Temporal (single-channel) ICA and Spatio-Temporal ICA. These techniques are based on information derived from both multi-channel as well as single channel biomedical signal recordings. We assess the suitability of the three techniques in isolating and extracting out epileptic seizure sources. Although our results are preliminary in nature, we show that standard implementations of ICA (ensemble ICA) are lacking when attempting to extract complex underlying activity such as ictal activity in the EEG. Temporal ICA performs well in separating underlying sources, although it is clearly lacking in spatial information. Spatio-Temporal ICA has the advantage of using temporal information to inform the ICA process, aided by the spatial information inherent in multi-channel recordings. This work is being expanded for seizure onset analysis through scalp EEG.
Keywords
Biomedical signal processing; Data mining; Electroencephalography; Epilepsy; Independent component analysis; Information analysis; Scalp; Signal processing algorithms; Source separation; Spatial filters; Algorithms; Artificial Intelligence; Diagnosis, Computer-Assisted; Electroencephalography; Epilepsy; Humans; Pattern Recognition, Automated; Principal Component Analysis; Reproducibility of Results; Sensitivity and Specificity;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location
Vancouver, BC
ISSN
1557-170X
Print_ISBN
978-1-4244-1814-5
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2008.4649919
Filename
4649919
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