Online detection of error-related potentials boosts the performance of mental typewriters

<p>Abstract</p> <p>Background</p> <p>Increasing the communication speed of brain-computer interfaces (BCIs) is a major aim of current BCI-research. The idea to automatically detect error-related potentials (ErrPs) in order to veto erroneous decisions of a BCI has been e...

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Main Authors: Schmidt Nico M, Blankertz Benjamin, Treder Matthias S
Format: Article
Language:English
Published: BMC 2012-02-01
Series:BMC Neuroscience
Subjects:
Online Access:http://www.biomedcentral.com/1471-2202/13/19
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spelling doaj-2b74b3ec68b64ad3b4cc5754956ff4402020-11-24T22:00:49ZengBMCBMC Neuroscience1471-22022012-02-011311910.1186/1471-2202-13-19Online detection of error-related potentials boosts the performance of mental typewritersSchmidt Nico MBlankertz BenjaminTreder Matthias S<p>Abstract</p> <p>Background</p> <p>Increasing the communication speed of brain-computer interfaces (BCIs) is a major aim of current BCI-research. The idea to automatically detect error-related potentials (ErrPs) in order to veto erroneous decisions of a BCI has been existing for more than one decade, but this approach was so far little investigated in online mode.</p> <p>Methods</p> <p>In our study with eleven participants, an ErrP detection mechanism was implemented in an electroencephalography (EEG) based gaze-independent visual speller.</p> <p>Results</p> <p>Single-trial ErrPs were detected with a mean accuracy of 89.1% (AUC 0.90). The spelling speed was increased on average by 49.0% using ErrP detection. The improvement in spelling speed due to error detection was largest for participants with low spelling accuracy.</p> <p>Conclusion</p> <p>The performance of BCIs can be increased by using an automatic error detection mechanism. The benefit for patients with motor disorders is potentially high since they often have rather low spelling accuracies compared to healthy people.</p> http://www.biomedcentral.com/1471-2202/13/19Brain-computer interfaceElectroencephalographyERP-SpellerError-related potentialsInformation transfer rate
collection DOAJ
language English
format Article
sources DOAJ
author Schmidt Nico M
Blankertz Benjamin
Treder Matthias S
spellingShingle Schmidt Nico M
Blankertz Benjamin
Treder Matthias S
Online detection of error-related potentials boosts the performance of mental typewriters
BMC Neuroscience
Brain-computer interface
Electroencephalography
ERP-Speller
Error-related potentials
Information transfer rate
author_facet Schmidt Nico M
Blankertz Benjamin
Treder Matthias S
author_sort Schmidt Nico M
title Online detection of error-related potentials boosts the performance of mental typewriters
title_short Online detection of error-related potentials boosts the performance of mental typewriters
title_full Online detection of error-related potentials boosts the performance of mental typewriters
title_fullStr Online detection of error-related potentials boosts the performance of mental typewriters
title_full_unstemmed Online detection of error-related potentials boosts the performance of mental typewriters
title_sort online detection of error-related potentials boosts the performance of mental typewriters
publisher BMC
series BMC Neuroscience
issn 1471-2202
publishDate 2012-02-01
description <p>Abstract</p> <p>Background</p> <p>Increasing the communication speed of brain-computer interfaces (BCIs) is a major aim of current BCI-research. The idea to automatically detect error-related potentials (ErrPs) in order to veto erroneous decisions of a BCI has been existing for more than one decade, but this approach was so far little investigated in online mode.</p> <p>Methods</p> <p>In our study with eleven participants, an ErrP detection mechanism was implemented in an electroencephalography (EEG) based gaze-independent visual speller.</p> <p>Results</p> <p>Single-trial ErrPs were detected with a mean accuracy of 89.1% (AUC 0.90). The spelling speed was increased on average by 49.0% using ErrP detection. The improvement in spelling speed due to error detection was largest for participants with low spelling accuracy.</p> <p>Conclusion</p> <p>The performance of BCIs can be increased by using an automatic error detection mechanism. The benefit for patients with motor disorders is potentially high since they often have rather low spelling accuracies compared to healthy people.</p>
topic Brain-computer interface
Electroencephalography
ERP-Speller
Error-related potentials
Information transfer rate
url http://www.biomedcentral.com/1471-2202/13/19
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