Spatial and spectral features fusion for EEG classification during motor imagery in BCI

@article{Tan2017SpatialAS,
  title={Spatial and spectral features fusion for EEG classification during motor imagery in BCI},
  author={Chuanqi Tan and Fuchun Sun and Wenchang Zhang and Shaobo Liu and Chunfang Liu},
  journal={2017 IEEE EMBS International Conference on Biomedical \& Health Informatics (BHI)},
  year={2017},
  pages={309-312}
}
  • Chuanqi Tan, F. Sun, +2 authors Chunfang Liu
  • Published 6 August 2018
  • Computer Science, Mathematics, Biology, Engineering
  • 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)
Brain computer interface (BCI) is the only way for some special patients to communicate with the outside world and provide a direct control channel between brain and the external devices. As a non-invasive interface, the scalp electroencephalography (EEG) has a significant potential to be a major input signal for future BCI systems. Traditional methods only focus on a particular feature in the EEG signal, which limits the practical applications of EEG-based BCI. In this paper, we propose a… 
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