Response error correction: A demonstration of improved human-machine performance using real-time EEG monitoring

L. Parra, C. Spence, Adam Gerson, Paul Sajda

We describe a brain-computer interface (BCI) system, which uses a set of adaptive linear preprocessing and classification algorithms for single-trial detection of error related negativity (ERN). We use the detected ERN as an estimate of a subject’s perceived error during an alternative forced choice visual discrimination task. The detected ERN is used to correct subject errors. Our initial results show average improvement in subject performance of 21% when errors are automatically corrected via the BCI. We are currently investigating the generalization of the overall approach to other tasks and stimulus paradigms.

Available Online https://www.ncbi.nlm.nih.gov/pubmed/12899266
Accepted 1 June 2003
Download Now

Latest News & Links

See All News