AnEnsemble De-Noising Method for Spatio-Temporal EEG / MEG Data


Weiss, S, Leahy, R M, Mosher, J C and Stewart, R W (1997) AnEnsemble De-Noising Method for Spatio-Temporal EEG / MEG Data. Applied Signal Processing, 4, (3), 142-153.

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Description/Abstract

EEG/MEG are important tools for non-invasive medical diagnosis and basic studies of the brain and its functioning, but often applications are limited due to a very low SNR in the data. Here, we present a discrete wavelet transform (DWT) based de-noising method for spatio-temporal EEG/MEG measurements collected by a sensor array. A robust threshold selection can be achieved by incorporating spatial information and pre-stimulus data to estimate signal and noise energies. Further improvement can be gained by applying a translation-invariant approach to the derived de-noising scheme. In simulations, the performance of the proposed method is evaluated in comparison to standard de-noising and low-rank approximation, which offers some complementarity to our approach.

Item Type: Article
ISSNs: 0941-0635
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science
ePrint ID: 251912
Date Deposited: 11 Dec 2003
Last Modified: 27 Mar 2014 19:53
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/251912

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