Literature DB >> 21096199

A novel brain-computer interface based on the rapid serial visual presentation paradigm.

Laura Acqualagna1, Matthias Sebastian Treder, Martijn Schreuder, Benjamin Blankertz.   

Abstract

Most present-day visual brain computer interfaces (BCIs) suffer from the fact that they rely on eye movements, are slow-paced, or feature a small vocabulary. As a potential remedy, we explored a novel BCI paradigm consisting of a central rapid serial visual presentation (RSVP) of the stimuli. It has a large vocabulary and realizes a BCI system based on covert non-spatial selective visual attention. In an offline study, eight participants were presented sequences of rapid bursts of symbols. Two different speeds and two different color conditions were investigated. Robust early visual and P300 components were elicited time-locked to the presentation of the target. Offline classification revealed a mean accuracy of up to 90% for selecting the correct symbol out of 30 possibilities. The results suggest that RSVP-BCI is a promising new paradigm, also for patients with oculomotor impairments.

Entities:  

Mesh:

Year:  2010        PMID: 21096199     DOI: 10.1109/IEMBS.2010.5626548

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  25 in total

Review 1.  Human visual skills for brain-computer interface use: a tutorial.

Authors:  Melanie Fried-Oken; Michelle Kinsella; Betts Peters; Brandon Eddy; Bruce Wojciechowski
Journal:  Disabil Rehabil Assist Technol       Date:  2020-06-01

2.  An Active RBSE Framework to Generate Optimal Stimulus Sequences in a BCI for Spelling.

Authors:  Mohammad Moghadamfalahi; Murat Akcakaya; Hooman Nezamfar; Jamshid Sourati; Deniz Erdogmus
Journal:  IEEE Trans Signal Process       Date:  2017-07-17       Impact factor: 4.931

3.  Probabilistic Simulation Framework for EEG-Based BCI Design.

Authors:  Umut Orhan; Hooman Nezamfar; Murat Akcakaya; Deniz Erdogmus; Matt Higger; Mohammad Moghadamfalahi; Andrew Fowler; Brian Roark; Barry Oken; Melanie Fried-Oken
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2016-12-05

4.  Pyff - a pythonic framework for feedback applications and stimulus presentation in neuroscience.

Authors:  Bastian Venthur; Simon Scholler; John Williamson; Sven Dähne; Matthias S Treder; Maria T Kramarek; Klaus-Robert Müller; Benjamin Blankertz
Journal:  Front Neurosci       Date:  2010-12-02       Impact factor: 4.677

5.  An Event-Driven AR-Process Model for EEG-Based BCIs With Rapid Trial Sequences.

Authors:  Paula Gonzalez-Navarro; Yeganeh M Marghi; Bahar Azari; Murat Akcakaya; Deniz Erdogmus
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2019-03-08       Impact factor: 3.802

6.  Spatio-Temporal EEG Models for Brain Interfaces.

Authors:  P Gonzalez-Navarro; M Moghadamfalahi; M Akcakaya; D Erdogmus
Journal:  Signal Processing       Date:  2016-08-06       Impact factor: 4.662

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

Authors:  Nico M Schmidt; Benjamin Blankertz; Matthias S Treder
Journal:  BMC Neurosci       Date:  2012-02-15       Impact factor: 3.288

8.  Listen, You are Writing! Speeding up Online Spelling with a Dynamic Auditory BCI.

Authors:  Martijn Schreuder; Thomas Rost; Michael Tangermann
Journal:  Front Neurosci       Date:  2011-10-14       Impact factor: 4.677

9.  Subliminal salience search illustrated: EEG identity and deception detection on the fringe of awareness.

Authors:  Howard Bowman; Marco Filetti; Dirk Janssen; Li Su; Abdulmajeed Alsufyani; Brad Wyble
Journal:  PLoS One       Date:  2013-01-23       Impact factor: 3.240

10.  The cost of space independence in P300-BCI spellers.

Authors:  Srivas Chennu; Abdulmajeed Alsufyani; Marco Filetti; Adrian M Owen; Howard Bowman
Journal:  J Neuroeng Rehabil       Date:  2013-07-29       Impact factor: 4.262

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