• DocumentCode
    2223016
  • Title

    Unsupervised adaptive GMM for BCI

  • Author

    Hasan, Bashar Awwad Shiekh ; Gan, John Q.

  • Author_Institution
    Brain-Comput. Interfaces Group, Univ. of Essex, Colchester
  • fYear
    2009
  • fDate
    April 29 2009-May 2 2009
  • Firstpage
    295
  • Lastpage
    298
  • Abstract
    An unsupervised adaptive Gaussian mixture model is introduced for online brain-computer interfaces (BCI). The method is tested on two BCI data sets, demonstrating significant performance improvement in comparison with a static model.
  • Keywords
    Gaussian distribution; brain-computer interfaces; unsupervised learning; BCI; online brain-computer interfaces; static model; unsupervised adaptive Gaussian mixture model; Adaptation model; Bayesian methods; Brain computer interfaces; Brain modeling; Electroencephalography; Gallium nitride; Neural engineering; Probability; Random variables; Testing; Gaussian mixture models; adaptive BCI; unsupervised adaptation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Engineering, 2009. NER '09. 4th International IEEE/EMBS Conference on
  • Conference_Location
    Antalya
  • Print_ISBN
    978-1-4244-2072-8
  • Electronic_ISBN
    978-1-4244-2073-5
  • Type

    conf

  • DOI
    10.1109/NER.2009.5109291
  • Filename
    5109291
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2223016