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Conference Papers Year : 2010

Wavelet denoising for P300 single-trial detection

Laurent Bougrain


Template-based analysis techniques are good candidates to robustly detect transient temporal graphic elements (e.g. event-related potential, k-complex, sleep spindles, vertex waves, spikes) in noisy and multi-sources electro-encephalographic signals. More specifically, we present the impact on a large dataset of a wavelet denoising to detect evoked potentials in a single-trial P300 speller. Using coiflets as a denoising process allows to obtain more stable accurracies for all subjects.
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inria-00549218 , version 1 (21-12-2010)


  • HAL Id : inria-00549218 , version 1


Carolina Saavedra, Laurent Bougrain. Wavelet denoising for P300 single-trial detection. Proccedings of the 5th french conference on computational neuroscience - Neurocomp'10, Oct 2010, Lyon, France. pp.227-231. ⟨inria-00549218⟩
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