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Time adaptive denoising of single trial event- related potentials in the wavelet domain

Published online by Cambridge University Press:  15 December 2000

ARNDT EFFERN ,
KLAUS LEHNERTZ ,
THOMAS GRUNWALD ,
GUILLÉN FERNÁNDEZ ,
PETER DAVID  and
CHRISTIAN E. ELGER
ARNDT EFFERN
Affiliation:
Epileptology, University of Bonn, Germany Radiation and Nuclear Physics, University of Bonn, Germany
KLAUS LEHNERTZ
Affiliation:
Epileptology, University of Bonn, Germany
THOMAS GRUNWALD
Affiliation:
Epileptology, University of Bonn, Germany
GUILLÉN FERNÁNDEZ
Affiliation:
Epileptology, University of Bonn, Germany
PETER DAVID
Affiliation:
Radiation and Nuclear Physics, University of Bonn, Germany
CHRISTIAN E. ELGER
Affiliation:
Epileptology, University of Bonn, Germany
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Abstract

We present a new wavelet-based method for single trial analysis of transient and time variant event-related potentials (ERPs). Expecting more accurate filter settings than achieved by other techniques (low-pass filter, a posteriori Wiener filter, time invariant wavelet filter), ERPs were initially balanced in time. By simulation, better filter performance could be established for test signals contaminated with either white noise or isospectral noise. To provide an example of real application, the method was applied to limbic P300 potentials (MTL-P300). As a result, variance of single trial MTL-P300s decreased, without restricting the corresponding mean. The proposed method can be regarded as an alternative for single-trial ERP analysis.

Keywords

ERPWoody filterNonlinearWavelet shrinkage
Type
Research Article
Information
Psychophysiology , Volume 37 , Issue 6 , November 2000 , pp. 859 - 865
Copyright
2000 Society for Psychophysiological Research

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