• DocumentCode
    1814112
  • Title

    Multifeature Analysis in Motor Imagery EEG Classification

  • Author

    Jian-feng, Hu

  • Author_Institution
    Inst. of Inf. Technol., Jiangxi Blue Sky Univ., Nanchang, China
  • fYear
    2010
  • fDate
    29-31 July 2010
  • Firstpage
    114
  • Lastpage
    117
  • Abstract
    Classification of EEG signals is core issues on EEG-based brain-computer interface (BCI). Typically, such classification has been performed using features extracted from EEG signals. Many features have proved to be unique enough to used in BCI application. However, different features show different discriminative power for different subjects or different trials. In this paper, multifeature was used to improve the system performance.
  • Keywords
    bioelectric phenomena; brain-computer interfaces; electroencephalography; feature extraction; neurophysiology; signal processing; wavelet transforms; EEG signal; brain computer interface; electroencephalogram; feature extraction; motor imagery; multifeature analysis; Brain computer interfaces; Brain models; Electroencephalography; Entropy; Feature extraction; Support vector machine classification; Brain-Computer Interface (BCI); Motor Imagery; Multifeature Electroencephalogram (EEG);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Commerce and Security (ISECS), 2010 Third International Symposium on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-1-4244-8231-3
  • Electronic_ISBN
    978-1-4244-8231-3
  • Type

    conf

  • DOI
    10.1109/ISECS.2010.33
  • Filename
    5557424
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1814112