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.
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.
|Divisions:||Faculty of Physical and Applied Science > Electronics and Computer Science
|Date Deposited:||11 Dec 2003|
|Last Modified:||02 Mar 2012 13:18|
|Contributors:||Weiss, S (Author)
Leahy, R M (Author)
Mosher, J C (Author)
Stewart, R W (Author)
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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