Motor imagery classification via combinatory decomposition of ERP and ERSP using sparse nonnegative matrix factorization.

@article{Lu2015MotorIC,
  title={Motor imagery classification via combinatory decomposition of ERP and ERSP using sparse nonnegative matrix factorization.},
  author={Na Lu and Tao Yin},
  journal={Journal of neuroscience methods},
  year={2015},
  volume={249},
  pages={41-9}
}
BACKGROUND Brain activities could be measured by devices like EEG, MEG, MRI etc. in terms of electric or magnetic signal, which could provide information from three domains, i.e., time, frequency and space. Combinatory analysis of these features could definitely help to improve the classification performance on brain activities. NMF (nonnegative matrix factorization) has been widely applied in pattern extraction tasks (e.g., face recognition, gene data analysis) which could provide physically… CONTINUE READING