Classification of Motor Imagery Tasks by means of Time-Frequency-Spatial Analysis for Brain-Computer Interface Applications

@article{Qin2005ClassificationOM,
  title={Classification of Motor Imagery Tasks by means of Time-Frequency-Spatial Analysis for Brain-Computer Interface Applications},
  author={Lihong Qin and Baharan Kamousi and Zhuo Liu and Li-liang Ding and Bin He},
  journal={Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005.},
  year={2005},
  pages={374-376}
}
We have developed new algorithms for classification of motor imagery tasks for brain-computer interface applications by analyzing single trial scalp EEG signals in the time-, frequency-, and space-domains. These new algorithms have been evaluated using a publically available dataset. The results are promising, suggesting that the newly developed algorithms may provide useful alternative for noninvasive brain-computer interface applications 

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