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Online Detection of P300 and Error Potentials in a BCI Speller

Error potentials (ErrPs), that is, alterations of the EEG traces related to the subject perception of erroneous responses, have been suggested to be an elegant way to recognize misinterpreted commands in brain-computer interface (BCI) systems. We implemented a P300-based BCI speller that uses a gene...

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Detalles Bibliográficos
Autores principales: Dal Seno, Bernardo, Matteucci, Matteo, Mainardi, Luca
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2821756/
https://www.ncbi.nlm.nih.gov/pubmed/20169142
http://dx.doi.org/10.1155/2010/307254
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author Dal Seno, Bernardo
Matteucci, Matteo
Mainardi, Luca
author_facet Dal Seno, Bernardo
Matteucci, Matteo
Mainardi, Luca
author_sort Dal Seno, Bernardo
collection PubMed
description Error potentials (ErrPs), that is, alterations of the EEG traces related to the subject perception of erroneous responses, have been suggested to be an elegant way to recognize misinterpreted commands in brain-computer interface (BCI) systems. We implemented a P300-based BCI speller that uses a genetic algorithm (GA) to detect P300s, and added an automatic error-correction system (ECS) based on the single-sweep detection of ErrPs. The developed system was tested on-line on three subjects and here we report preliminary results. In two out of three subjects, the GA provided a good performance in detecting P300 (90% and 60% accuracy with 5 repetitions), and it was possible to detect ErrP with an accuracy (roughly 60%) well above the chance level. In our knowledge, this is the first time that ErrP detection is performed on-line in a P300-based BCI. Preliminary results are encouraging, but further refinements are needed to improve performances.
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spelling pubmed-28217562010-02-18 Online Detection of P300 and Error Potentials in a BCI Speller Dal Seno, Bernardo Matteucci, Matteo Mainardi, Luca Comput Intell Neurosci Research Article Error potentials (ErrPs), that is, alterations of the EEG traces related to the subject perception of erroneous responses, have been suggested to be an elegant way to recognize misinterpreted commands in brain-computer interface (BCI) systems. We implemented a P300-based BCI speller that uses a genetic algorithm (GA) to detect P300s, and added an automatic error-correction system (ECS) based on the single-sweep detection of ErrPs. The developed system was tested on-line on three subjects and here we report preliminary results. In two out of three subjects, the GA provided a good performance in detecting P300 (90% and 60% accuracy with 5 repetitions), and it was possible to detect ErrP with an accuracy (roughly 60%) well above the chance level. In our knowledge, this is the first time that ErrP detection is performed on-line in a P300-based BCI. Preliminary results are encouraging, but further refinements are needed to improve performances. Hindawi Publishing Corporation 2010 2010-02-11 /pmc/articles/PMC2821756/ /pubmed/20169142 http://dx.doi.org/10.1155/2010/307254 Text en Copyright © 2010 Bernardo Dal Seno et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Dal Seno, Bernardo
Matteucci, Matteo
Mainardi, Luca
Online Detection of P300 and Error Potentials in a BCI Speller
title Online Detection of P300 and Error Potentials in a BCI Speller
title_full Online Detection of P300 and Error Potentials in a BCI Speller
title_fullStr Online Detection of P300 and Error Potentials in a BCI Speller
title_full_unstemmed Online Detection of P300 and Error Potentials in a BCI Speller
title_short Online Detection of P300 and Error Potentials in a BCI Speller
title_sort online detection of p300 and error potentials in a bci speller
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2821756/
https://www.ncbi.nlm.nih.gov/pubmed/20169142
http://dx.doi.org/10.1155/2010/307254
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