A Study of the Effects of Electrode Number and Decoding Algorithm on Online EEG-Based BCI Behavioral Performance

@inproceedings{Meng2018ASO,
  title={A Study of the Effects of Electrode Number and Decoding Algorithm on Online EEG-Based BCI Behavioral Performance},
  author={Jianjun Meng and Bradley J. Edelman and Jaron Olsoe and Gabriel E Jacobs and Shuying Zhang and Angeliki Beyko and Bin He},
  booktitle={Front. Neurosci.},
  year={2018}
}
Motor imagery-based brain-computer interface (BCI) using electroencephalography (EEG) has demonstrated promising applications by directly decoding users' movement related mental intention. The selection of control signals, e.g., the channel configuration and decoding algorithm, plays a vital role in the online performance and progressing of BCI control. While several offline analyses report the effect of these factors on BCI accuracy for a single session-performance increases asymptotically by… CONTINUE READING