NDLI: A method for the blind separation of sources for use as the first stage of a neonatal seizure detection system

Content Provider	IEEE Xplore Digital Library
Author	Faul, S. Marnane, L. Lightbody, G. Boylan, G. Connolly, S.
Copyright Year	2005
Description	Author affiliation: Dept. of Electr. and Electron. Eng., Univ. Coll. Cork, Cork, Ireland (Faul, S.; Marnane, L.; Lightbody, G.)
Abstract	A method is proposed for automatically choosing independent components (ICs) of interest from neonatal EEG data, with the aim of using them in further analysis to detect seizures. This procedure greatly reduces the amount of information which needs to be processed in the seizure detection system, and reduces the effect of noise and artefacts on its performance. The fast ICA algorithm is used to generate the ICs, and the complexity of each IC is examined to determine those of interest. The singular value fraction (SVF) measure is used to reduce the number of sources containing artefacts chosen. In the best case, the 12 channel EEG used in these tests is reduced to 2 or 3 sources of interest. In every case, at least 3 sources were removed that consisted of noise.
Sponsorship	IEEE Signal Processing Soc
File Size	728794
File Format	PDF
ISBN	0780388747
ISSN	15206149
DOI	10.1109/ICASSP.2005.1416327
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-03-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pediatrics Independent component analysis Electroencephalography Principal component analysis Data engineering Educational institutions Hospitals Noise reduction Integrated circuit noise Testing
Content Type	Text
Resource Type	Article

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