id: 05985015
dt: a
an: 05985015
au: Jin, Jing; Zhang, Yu; Wang, Xingyu
ti: A novel combination of time phase and EEG frequency components for
    SSVEP-based BCI.
so: Lu, Bao-Liang (ed.) et al., Neural information processing. 18th
    international conference, ICONIP 2011, Shanghai, China, November
    13‒17, 2011. Proceedings, Part I. Berlin: Springer (ISBN
    978-3-642-24954-9/pbk). Lecture Notes in Computer Science 7062, 273-278
    (2011).
py: 2011
pu: Berlin: Springer
la: EN
cc: 
ut: brain-computer interfaces (BCIs); electroencephalogram (EEG); steady-state
    visual evoked potential (SSVEP); time phase
ci: 
li: doi:10.1007/978-3-642-24955-6_33
ab: Summary: The steady-state visual evoked potential (SSVEP) has been widely
    applied in brain-computer interfaces (BCIs), such as letter or icon
    selection and device control. Most of these BCIs used different
    flickering frequencies to evoke SSVEP with different frequency
    components that were used as control commands. In this paper, a novel
    method combining the time phase and EEG frequency components is
    presented and validated with nine healthy subjects. In this method,
    four different frequency components of EEG were classified out from
    four time phases. When the SSVEP is evoked and what is the frequency of
    the SSVEP is determined by the linear discriminant analysis (LDA)
    classifier in the same time to locate the target image. The results
    from offline analysis show that this method yields good performance
    both in classification accuracy and information transfer rate (ITR).
rv: