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xDAWN algorithm to enhance evoked potentials: application to brain-computer interface.

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  • معلومة اضافية
    • Contributors:
      GIPSA - Machines Parlantes, Agents Communicants & Interaction Face-à-face (GIPSA-MPACIF); Département Parole et Cognition (GIPSA-DPC); Grenoble Images Parole Signal Automatique (GIPSA-lab); Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab); Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS); Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)); Direction de Recherche Technologique (CEA) (DRT (CEA)); Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA); Dynamique Cérébrale et Cognition; Université Claude Bernard Lyon 1 (UCBL); Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)
    • بيانات النشر:
      CCSD
      Institute of Electrical and Electronics Engineers (IEEE)
      Institute of Electrical and Electronics Engineers
    • الموضوع:
      2009
    • Collection:
      HAL-CEA (Commissariat à l'énergie atomique et aux énergies alternatives)
    • نبذة مختصرة :
      International audience ; A brain-computer interface (BCI) is a communication system that allows to control a computer or any other device thanks to the brain activity. The BCI described in this paper is based on the P300 speller BCI paradigm introduced by Farwell and Donchin . An unsupervised algorithm is proposed to enhance P300 evoked potentials by estimating spatial filters; the raw EEG signals are then projected into the estimated signal subspace. Data recorded on three subjects were used to evaluate the proposed method. The results, which are presented using a Bayesian linear discriminant analysis classifier , show that the proposed method is efficient and accurate.
    • Relation:
      info:eu-repo/semantics/altIdentifier/pmid/19174332; PUBMED: 19174332
    • الرقم المعرف:
      10.1109/TBME.2009.2012869
    • الدخول الالكتروني :
      https://hal.science/hal-00454568
      https://hal.science/hal-00454568v1/document
      https://hal.science/hal-00454568v1/file/2009_IEEE_BME.pdf
      https://doi.org/10.1109/TBME.2009.2012869
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.2D04E795