Fusion with language models improves spelling accuracy for ERP-based brain computer interface spellers

@article{Orhan2011FusionWL,
  title={Fusion with language models improves spelling accuracy for ERP-based brain computer interface spellers},
  author={Umut Orhan and Deniz Erdogmus and Brian Roark and Shalini Purwar and Kenneth E. Hild and Barry S Oken and Hooman Nezamfar and Melanie Fried-Oken},
  journal={2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  year={2011},
  pages={5774-5777}
}
Event related potentials (ERP) corresponding to a stimulus in electroencephalography (EEG) can be used to detect the intent of a person for brain computer interfaces (BCI). This paradigm is widely utilized to build letter-by-letter text input systems using BCI. Nevertheless using a BCI-typewriter depending only on EEG responses will not be sufficiently accurate for single-trial operation in general, and existing systems utilize many-trial schemes to achieve accuracy at the cost of speed. Hence… CONTINUE READING
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