Estimation of individual evoked potential by wavelet transform

ISBN : 978-2-9532965-0-1A new method to improve the signal-to-noise ratio of single evoked potentials (EP) measurements is presented, in which, contrary to previous methods, no a priori assumptions on the signal are necessary. This method is based on the wavelets decomposition of the individual signals. A statistical thresholding is applied on the coefficients of the decomposition: we estimate whether the mean value of the coefficients across trials and for each time point is significantly different from a random estimate. The performance of the method is evaluated with simulation and the method is applied to real dat

Statistical Method to Extract Evoked Potentials from Noise

Evoked Potentials are induced by visual or auditory stimulation. The Evoked Potentials represent transient electrical activities of some limited brain regions. The signal-noise ratio (SNR) of the EPs is typically around -10 dB. In order to study brain activities related to information processing in the brain, one has to “extract” the single EPs from the noise. We propose a method does not require a priori information concerning the characteristics (time, frequency) of the signal and does not use a template. The method proposed in this work use the wavelet transform associated with a statistical test

Wavelets statistical denoising (WaSDe): individual evoked potential extraction by multi-resolution wavelets decomposition and bootstrap

International audienceThe present study aims at developing a method to extract single sweep event-related potentials obtained with Eriksen's flanker task. Unlike previous methods, no a priori assumptions on the characteristics of signal and noise are necessary. The method is based on the wavelet decomposition, bootstrap and a statistical determination of the reliable frequency coefficients across the individual signals at each time point: significant coefficients will be conserved, whereas the other ones will be set to zero. After removing the unsystematic coefficients (i.e. the noise), the signal is reconstructed, allowing to keep only the components of the event-related potentials. The performances of the method are evaluated with both simulated data and real event-related potential recordings, and compared with other methods