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Open Access Highly Accessed Research article

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

Nico M Schmidt12*, Benjamin Blankertz1 and Matthias S Treder1

Author Affiliations

1 Machine Learning Laboratory, Berlin Institute of Technology, Berlin, Germany

2 Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Switzerland, Andreasstrasse 15, 8050 Zurich, Switzerland

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BMC Neuroscience 2012, 13:19  doi:10.1186/1471-2202-13-19

Published: 15 February 2012

Abstract

Background

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.

Methods

In our study with eleven participants, an ErrP detection mechanism was implemented in an electroencephalography (EEG) based gaze-independent visual speller.

Results

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.

Conclusion

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.

Keywords:
Brain-computer interface; Electroencephalography; ERP-Speller; Error-related potentials; Information transfer rate