Skip to Main content Skip to Navigation
Conference papers

Wavelet-based Semblance for P300 Single-trial Detection

Carolina Saavedra 1 Laurent Bougrain 1, *
* Corresponding author
1 NEUROSYS - Analysis and modeling of neural systems by a system neuroscience approach
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
Abstract : Electroencephalographic signals are usually contaminated by noise and artifacts making difficult to detect Event-Related Potential (ERP), specially in single trials. Wavelet denoising has been successfully applied to ERP detection, but usually works using channels information independently. This paper presents a new adaptive approach to denoise signals taking into account channels correlation in the wavelet domain. Moreover, we combine phase and amplitude information in the wavelet domain to automatically select a temporal window which increases class separability. Results on a classic Brain-Computer Interface application to spell characters using P300 detection show that our algorithm has a better accuracy with respect to the VisuShrink wavelet technique and XDAWN algorithm among 22 healthy subjects, and a better regularity than XDAWN.
Complete list of metadata

Cited literature [14 references]  Display  Hide  Download
Contributor : Carolina Saavedra Connect in order to contact the contributor
Submitted on : Friday, November 23, 2012 - 11:52:12 AM
Last modification on : Saturday, October 16, 2021 - 11:26:09 AM
Long-term archiving on: : Sunday, February 24, 2013 - 3:48:46 AM


Files produced by the author(s)


  • HAL Id : hal-00756563, version 1



Carolina Saavedra, Laurent Bougrain. Wavelet-based Semblance for P300 Single-trial Detection. BIOSIGNAL - international conference on Bio-Inspired Systems and Signal Processing - 2013, Feb 2013, Barcelone, Spain. ⟨hal-00756563⟩



Les métriques sont temporairement indisponibles