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.


[img] PDF
Download (216Kb)
[img] Postscript
Download (216Kb)


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
Accepted Date and Publication Date:
Date Deposited: 11 Dec 2003
Last Modified: 27 Mar 2014 19:53
Further Information:Google Scholar

Actions (login required)

View Item View Item

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