Literature DB >> 21555847

SSVEP-based Bremen-BCI interface--boosting information transfer rates.

Ivan Volosyak1.   

Abstract

In recent years, there has been increased interest in using steady-state visual evoked potentials (SSVEP) in brain-computer interface (BCI) systems; the SSVEP approach currently provides the fastest and most reliable communication paradigm for the implementation of a non-invasive BCI. This paper presents recent developments in the signal processing of the SSVEP-based Bremen BCI system, which allowed one of the subjects in an online experiment to reach a peak information transfer rate (ITR) of 124 bit min(-1). It is worth mentioning that this ITR value is higher than all values previously published in the literature for any kind of BCI paradigm.

Mesh:

Year:  2011        PMID: 21555847     DOI: 10.1088/1741-2560/8/3/036020

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  31 in total

1.  The performance of 9-11-year-old children using an SSVEP-based BCI for target selection.

Authors:  James J S Norton; Jessica Mullins; Birgit E Alitz; Timothy Bretl
Journal:  J Neural Eng       Date:  2018-06-28       Impact factor: 5.379

2.  Recursive Bayesian Coding for BCIs.

Authors:  Matt Higger; Fernando Quivira; Murat Akcakaya; Mohammad Moghadamfalahi; Hooman Nezamfar; Mujdat Cetin; Deniz Erdogmus
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2016-07-13       Impact factor: 3.802

3.  Plug&Play Brain-Computer Interfaces for effective Active and Assisted Living control.

Authors:  Niccolò Mora; Ilaria De Munari; Paolo Ciampolini; José Del R Millán
Journal:  Med Biol Eng Comput       Date:  2016-11-17       Impact factor: 2.602

4.  Performance assessment in brain-computer interface-based augmentative and alternative communication.

Authors:  David E Thompson; Stefanie Blain-Moraes; Jane E Huggins
Journal:  Biomed Eng Online       Date:  2013-05-16       Impact factor: 2.819

5.  A multimenu system based on the P300 component as a time saving procedure for communication with a brain-computer interface.

Authors:  Joanna Jarmolowska; Marcello M Turconi; Pierpaolo Busan; Jie Mei; Piero P Battaglini
Journal:  Front Neurosci       Date:  2013-03-25       Impact factor: 4.677

6.  Online adaptation of a c-VEP Brain-computer Interface(BCI) based on error-related potentials and unsupervised learning.

Authors:  Martin Spüler; Wolfgang Rosenstiel; Martin Bogdan
Journal:  PLoS One       Date:  2012-12-07       Impact factor: 3.240

Review 7.  From spinal central pattern generators to cortical network: integrated BCI for walking rehabilitation.

Authors:  G Cheron; M Duvinage; C De Saedeleer; T Castermans; A Bengoetxea; M Petieau; K Seetharaman; T Hoellinger; B Dan; T Dutoit; F Sylos Labini; F Lacquaniti; Y Ivanenko
Journal:  Neural Plast       Date:  2012-01-04       Impact factor: 3.599

8.  Broad-Band Visually Evoked Potentials: Re(con)volution in Brain-Computer Interfacing.

Authors:  Jordy Thielen; Philip van den Broek; Jason Farquhar; Peter Desain
Journal:  PLoS One       Date:  2015-07-24       Impact factor: 3.240

9.  On the quantification of SSVEP frequency responses in human EEG in realistic BCI conditions.

Authors:  Rafał Kuś; Anna Duszyk; Piotr Milanowski; Maciej Łabęcki; Maria Bierzyńska; Zofia Radzikowska; Magdalena Michalska; Jarosław Zygierewicz; Piotr Suffczyński; Piotr Jerzy Durka
Journal:  PLoS One       Date:  2013-10-18       Impact factor: 3.240

10.  A BMI-based occupational therapy assist suit: asynchronous control by SSVEP.

Authors:  Takeshi Sakurada; Toshihiro Kawase; Kouji Takano; Tomoaki Komatsu; Kenji Kansaku
Journal:  Front Neurosci       Date:  2013-09-23       Impact factor: 4.677

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