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Extracting multisource brain activity from a single electromagnetic channel

James, C.J. and Lowe, D. (2003) Extracting multisource brain activity from a single electromagnetic channel Artificial Intelligence in Medicine, 28, (1), pp. 89-104. (doi:10.1016/S0933-3657(03)00037-X).

Record type: Article

Abstract

This paper develops a methodology for the extraction of multisource brain activity using only single channel recordings of electromagnetic (EM) brain signals. Measured electroencephalogram (EEG) and magnetoencephalogram (MEG) signals are used to demonstrate the utility of the method on extracting multisource activity from a single channel recording. At the heart of the method is dynamical embedding (DE) where first an appropriate embedding matrix is constructed out of a series of delay vectors from the measured signal. The embedding matrix contains the information we require, but in a mixed form which therefore needs to be deconstructed. In particular, we demonstrate how one form of independent component analysis (ICA) performed on the embedding matrix can deconstruct the single channel recording into its underlying informative components. The components are treated as a convenient expansion basis and subjective methods are then used to identify components of interest relevant to the application. The framework has been applied to single channels of both EEG and MEG recordings and is shown to isolate multiple sources of activity which includes: (i) artifactual components such as ocular, electrocardiographic and electrode artefact, (ii) seizure components in epileptic EEG recordings, and (iii) theta band, tumour related, activity in MEG recordings. The results are intuitive and meaningful in a neurophysiological setting.

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More information

Published date: May 2003
Keywords: electroencephalogram, magnetoencephalogram, independent component analysis, dynamical embedding, single channel analysis of electromagnetic brain signals

Identifiers

Local EPrints ID: 10976
URI: http://eprints.soton.ac.uk/id/eprint/10976
ISSN: 0933-3657
PURE UUID: 80c553f3-9b69-4f3f-81ef-8549b52a2895

Catalogue record

Date deposited: 13 Jun 2005
Last modified: 17 Jul 2017 17:05

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