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 EURASIP Journal on Applied Signal Processing, 4, (3), pp. 142-153.


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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 (print)
Organisations: Electronics & Computer Science
ePrint ID: 251912
Date :
Date Event
Date Deposited: 11 Dec 2003
Last Modified: 17 Apr 2017 23:39
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