Literature DB >> 15188881

BCI Competition 2003--Data set IIb: support vector machines for the P300 speller paradigm.

Matthias Kaper1, Peter Meinicke, Ulf Grossekathoefer, Thomas Lingner, Helge Ritter.   

Abstract

We propose an approach to analyze data from the P300 speller paradigm using the machine-learning technique support vector machines. In a conservative classification scheme, we found the correct solution after five repetitions. While the classification within the competition is designed for offline analysis, our approach is also well-suited for a real-world online solution: It is fast, requires only 10 electrode positions and demands only a small amount of preprocessing.

Mesh:

Year:  2004        PMID: 15188881     DOI: 10.1109/TBME.2004.826698

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  56 in total

1.  Predictive spelling with a P300-based brain-computer interface: Increasing the rate of communication.

Authors:  D B Ryan; G E Frye; G Townsend; D R Berry; S Mesa-G; N A Gates; E W Sellers
Journal:  Int J Hum Comput Interact       Date:  2011-01-01       Impact factor: 3.353

2.  Classification of multichannel EEG patterns using parallel hidden Markov models.

Authors:  Dror Lederman; Joseph Tabrikian
Journal:  Med Biol Eng Comput       Date:  2012-03-10       Impact factor: 2.602

Review 3.  Brain computer interfaces, a review.

Authors:  Luis Fernando Nicolas-Alonso; Jaime Gomez-Gil
Journal:  Sensors (Basel)       Date:  2012-01-31       Impact factor: 3.576

4.  A novel P300-based brain-computer interface stimulus presentation paradigm: moving beyond rows and columns.

Authors:  G Townsend; B K LaPallo; C B Boulay; D J Krusienski; G E Frye; C K Hauser; N E Schwartz; T M Vaughan; J R Wolpaw; E W Sellers
Journal:  Clin Neurophysiol       Date:  2010-03-26       Impact factor: 3.708

5.  Toward enhanced P300 speller performance.

Authors:  D J Krusienski; E W Sellers; D J McFarland; T M Vaughan; J R Wolpaw
Journal:  J Neurosci Methods       Date:  2007-08-01       Impact factor: 2.390

6.  Towards an independent brain-computer interface using steady state visual evoked potentials.

Authors:  Brendan Z Allison; Dennis J McFarland; Gerwin Schalk; Shi Dong Zheng; Melody Moore Jackson; Jonathan R Wolpaw
Journal:  Clin Neurophysiol       Date:  2008-02       Impact factor: 3.708

7.  Integrating language information with a hidden Markov model to improve communication rate in the P300 speller.

Authors:  William Speier; Corey Arnold; Jessica Lu; Aniket Deshpande; Nader Pouratian
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2014-01-21       Impact factor: 3.802

8.  Evaluating brain-computer interface performance using color in the P300 checkerboard speller.

Authors:  D B Ryan; G Townsend; N A Gates; K Colwell; E W Sellers
Journal:  Clin Neurophysiol       Date:  2017-08-08       Impact factor: 3.708

9.  Enhancing P300-BCI performance using latency estimation.

Authors:  Md Rakibul Mowla; Jane E Huggins; David E Thompson
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2017-06-28

10.  Bayesian approach to dynamically controlling data collection in P300 spellers.

Authors:  Chandra S Throckmorton; Kenneth A Colwell; David B Ryan; Eric W Sellers; Leslie M Collins
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2013-03-21       Impact factor: 3.802

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