EEG-Based Brain-Computer Interaction: Improved Accuracy by Automatic Single-Trial Error Detection

@inproceedings{Ferrez2007EEGBasedBI,
  title={EEG-Based Brain-Computer Interaction: Improved Accuracy by Automatic Single-Trial Error Detection},
  author={Pierre W. Ferrez and Jos{\'e} del R. Mill{\'a}n},
  booktitle={NIPS},
  year={2007}
}
Brain-computer interfaces (BCIs), as any other interaction modality based on physiological signals and body channels (e.g., muscular activity, speech and gestures), are prone to errors in the recognition of subject's intent. An elegant approach to improve the accuracy of BCIs consists in a verification procedure directly based on the presence of error-related potentials (ErrP) in the EEG recorded right after the occurrence of an error. Six healthy volunteer subjects with no prior BCI experience… CONTINUE READING

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Key Quantitative Results

  • We have achieved an average recognition rate of correct and erroneous single trials of 81.8% and 76.2%, respectively. Furthermore, we have achieved an average recognition rate of the subject's intent while trying to mentally drive the cursor of 73.1%.
  • These results show that single-trial recognition of erroneous and correct responses are above 75% and 80%, respectively.

Citations

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Error-related potential recorded by EEG in the context of a p300 mind speller brain-computer interface

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