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Blind source separation in single-channel EEG analysis: an application to BCI

Blind source separation in single-channel EEG analysis: an application to BCI
Blind source separation in single-channel EEG analysis: an application to BCI
In this work we present a technique for applying Blind Source Separation (BSS) to single channel recordings of Electromagnetic (EM) brain signals. Single channel recordings of brain signals are preprocessed through the method of delays, and the delay matrix processed with the BSS technique described here called LSDIAGtd which uses temporal decorrelation to implement the now popular Independent Component Analysis (ICA) algorithm. This allows the identification and extraction of statistically independent sources underlying these single channel recordings. In particular we depict the analysis of single channel recordings from a Brain-Computer Interfacing paradigm. We show that BSS technique applied in this way extracts a series of codebook vectors representing the spectral content underlying the recorded signal. It then becomes possible to identify and extract particular rhythmic activity underlying the recordings. We show that rhythmic activity in the 8 to 12Hz band can be extracted in the case of imagined hand movements for a particular BCI paradigm.
brain activity, eeg, bss, ica, method of delays, bci
4pp
Engineering in Medicine and Biology Society
James, C.J.
b3733b1f-a6a1-4c9b-b75c-6191d4142e52
Wang, S.
a2223997-9f42-425b-b0c6-1bcb64d9b8fc
James, C.J.
b3733b1f-a6a1-4c9b-b75c-6191d4142e52
Wang, S.
a2223997-9f42-425b-b0c6-1bcb64d9b8fc

James, C.J. and Wang, S. (2006) Blind source separation in single-channel EEG analysis: an application to BCI. In Proceedings 28th Annual International Conference IEEE Enginering in Medicine and Biology Society (EMBS). Engineering in Medicine and Biology Society. 4pp .

Record type: Conference or Workshop Item (Paper)

Abstract

In this work we present a technique for applying Blind Source Separation (BSS) to single channel recordings of Electromagnetic (EM) brain signals. Single channel recordings of brain signals are preprocessed through the method of delays, and the delay matrix processed with the BSS technique described here called LSDIAGtd which uses temporal decorrelation to implement the now popular Independent Component Analysis (ICA) algorithm. This allows the identification and extraction of statistically independent sources underlying these single channel recordings. In particular we depict the analysis of single channel recordings from a Brain-Computer Interfacing paradigm. We show that BSS technique applied in this way extracts a series of codebook vectors representing the spectral content underlying the recorded signal. It then becomes possible to identify and extract particular rhythmic activity underlying the recordings. We show that rhythmic activity in the 8 to 12Hz band can be extracted in the case of imagined hand movements for a particular BCI paradigm.

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More information

Published date: 2006
Additional Information: CD-ROM
Venue - Dates: 28th Annual International Conference IEEE Enginering in Medicine and Biology Society (EMBS), 2006-08-30 - 2006-09-03
Keywords: brain activity, eeg, bss, ica, method of delays, bci

Identifiers

Local EPrints ID: 43372
URI: https://eprints.soton.ac.uk/id/eprint/43372
PURE UUID: a3da47d7-3876-4aa8-9def-4a407573f7e4

Catalogue record

Date deposited: 08 Feb 2007
Last modified: 13 Mar 2019 21:09

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