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| Research article summary (published 30 May 2003): |
Response error correction--a demonstration of improved human-machine performance using real-time EEG monitoring.
Full Abstract
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.
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Author information
Author/s: Parra, Lucas C (LC); Spence, Clay D (CD); Gerson, Adam D (AD); Sajda, Paul (P);
Affiliation: Sarnoff Corporation, Princeton, NJ 08540, USA. lparra@sarnoff.com
Journal and publication information
Publication Type: Comparative Study; Evaluation Studies; Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Validation Studies
Journal: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society (IEEE Trans Neural Syst Rehabil Eng), published in United States. (Language: eng)
Reference: 2003-Jun; vol 11 (issue 2) : pp 173-7
Dates: Created 2003/08/05; Completed 2003/09/12; Revised 2006/11/15;
PMID: 12899266, status: MEDLINE (last retrieval date: 11/6/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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