The University of Southampton
University of Southampton Institutional Repository

Using dynamical embedding to isolate seizure components in the ictal EEG

Using dynamical embedding to isolate seizure components in the ictal EEG
Using dynamical embedding to isolate seizure components in the ictal EEG
A system for isolating seizure components in the epileptic electroencephalogram (EEG) is presented. The method of independent component analysis (ICA) is implemented to decompose multichannel recordings of scalp EEG known to contain epileptic seizures into their underlying independent components (ICs). The ICs are treated as a convenient expansion basis and in order to identify the relevant seizure components amongst the ICs, a series of dynamical embedding matrices are first constructed along each IC. By observing the change in structure of the singular spectra obtained by performing a singular value decomposition on each consecutive dynamical embedding matrix, it is possible to track changes in the underlying complexity of each IC with time. The change in complexity is linked to the change in entropy that can be calculated from each consecutive singular spectrum. The change in complexity, coupled with the topographical distribution of each IC, allows seizure-related components extracted by the ICA process to be subjectively identified. The method has been applied to four seizure EEG segments, and in each case probable seizure components were identified subjectively. As a proof-of-principle study, the method indicates that ICA coupled with dynamical embedding may be useful as a tool in pre-processing seizure EEG segments.
eeg analysis, consecutive dynamical embedding matrix, dynamical embedding, electrodiagnostics, proof-of-principle study, seizure components isolation, signal pre-processing, singular spectra, topographical distribution
1350-2344
315-320
James, C.J.
b3733b1f-a6a1-4c9b-b75c-6191d4142e52
Lowe, D.
3839d69d-7c99-4f4a-a37e-0a5731ff373b
James, C.J.
b3733b1f-a6a1-4c9b-b75c-6191d4142e52
Lowe, D.
3839d69d-7c99-4f4a-a37e-0a5731ff373b

James, C.J. and Lowe, D. (2000) Using dynamical embedding to isolate seizure components in the ictal EEG. IEE Proceedings - Science, Measurement and Technology, 147 (6), 315-320. (doi:10.1049/ip-smt:20000849).

Record type: Article

Abstract

A system for isolating seizure components in the epileptic electroencephalogram (EEG) is presented. The method of independent component analysis (ICA) is implemented to decompose multichannel recordings of scalp EEG known to contain epileptic seizures into their underlying independent components (ICs). The ICs are treated as a convenient expansion basis and in order to identify the relevant seizure components amongst the ICs, a series of dynamical embedding matrices are first constructed along each IC. By observing the change in structure of the singular spectra obtained by performing a singular value decomposition on each consecutive dynamical embedding matrix, it is possible to track changes in the underlying complexity of each IC with time. The change in complexity is linked to the change in entropy that can be calculated from each consecutive singular spectrum. The change in complexity, coupled with the topographical distribution of each IC, allows seizure-related components extracted by the ICA process to be subjectively identified. The method has been applied to four seizure EEG segments, and in each case probable seizure components were identified subjectively. As a proof-of-principle study, the method indicates that ICA coupled with dynamical embedding may be useful as a tool in pre-processing seizure EEG segments.

Full text not available from this repository.

More information

Published date: 2000
Keywords: eeg analysis, consecutive dynamical embedding matrix, dynamical embedding, electrodiagnostics, proof-of-principle study, seizure components isolation, signal pre-processing, singular spectra, topographical distribution

Identifiers

Local EPrints ID: 10799
URI: https://eprints.soton.ac.uk/id/eprint/10799
ISSN: 1350-2344
PURE UUID: 8e3e606f-0e18-431a-aea5-b9c94fecfc47

Catalogue record

Date deposited: 15 Jun 2005
Last modified: 15 Jul 2019 19:36

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×