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

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4 Author(s)
Parra, L.C. ; Sarnoff Corp., Princeton, NJ, USA ; Spence, C.D. ; Gerson, A.D. ; Sajda, P.

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.

Published in:

Neural Systems and Rehabilitation Engineering, IEEE Transactions on  (Volume:11 ,  Issue: 2 )