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), 89-104. (doi:10.1016/S0933-3657(03)00037-X).


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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.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1016/S0933-3657(03)00037-X
ISSNs: 0933-3657 (print)
Related URLs:
Keywords: electroencephalogram, magnetoencephalogram, independent component analysis, dynamical embedding, single channel analysis of electromagnetic brain signals
Subjects: R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
T Technology > TA Engineering (General). Civil engineering (General)
Q Science > QP Physiology
Divisions : University Structure - Pre August 2011 > Institute of Sound and Vibration Research > Signal Processing and Control
ePrint ID: 10976
Accepted Date and Publication Date:
May 2003Published
Date Deposited: 13 Jun 2005
Last Modified: 31 Mar 2016 11:21
URI: http://eprints.soton.ac.uk/id/eprint/10976

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