Literature DB >> 20569051

A new P300 stimulus presentation pattern for EEG-based spelling systems.

Jing Jin1, Petar Horki, Clemens Brunner, Xingyu Wang, Christa Neuper, Gert Pfurtscheller.   

Abstract

A P300 spelling system is one of the most popular EEG-based spelling systems. This system is normally presented as a matrix and allows its users to select one of many options by focused attention. It is possible to use large matrices as a large menu (computer keyboard, etc.), but then more time is required for each selection, because all rows and columns of the matrix must flash once per trial to locate the target character in the row/column (RC) speller method. In this paper, a new flash pattern design based on mathematical combinations is suggested. This new method decreases the number of flashes required in each trial. A typical example of a 6x6 matrix is considered. Only 9 flashes per trial for the 6x6 matrix are required in this new method, which is 3 flashes less than the RC speller method (12 flashes per trial). In this paper, practical bit rate was used. Results from offline analysis have shown that the 9-flash pattern yielded significantly higher practical bit rate than the 12-flash pattern (RC pattern).

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Year:  2010        PMID: 20569051     DOI: 10.1515/BMT.2010.029

Source DB:  PubMed          Journal:  Biomed Tech (Berl)        ISSN: 0013-5585            Impact factor:   1.411


  19 in total

1.  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

2.  Incorporating advanced language models into the P300 speller using particle filtering.

Authors:  W Speier; C W Arnold; A Deshpande; J Knall; N Pouratian
Journal:  J Neural Eng       Date:  2015-06-10       Impact factor: 5.379

3.  Online BCI Typing using Language Model Classifiers by ALS Patients in their Homes.

Authors:  William Speier; Nand Chandravadia; Dustin Roberts; S Pendekanti; Nader Pouratian
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2016-11-15

Review 4.  Integrating language models into classifiers for BCI communication: a review.

Authors:  W Speier; C Arnold; N Pouratian
Journal:  J Neural Eng       Date:  2016-05-06       Impact factor: 5.379

5.  The effects of stimulus timing features on P300 speller performance.

Authors:  Jessica Lu; William Speier; Xiao Hu; Nader Pouratian
Journal:  Clin Neurophysiol       Date:  2012-08-29       Impact factor: 3.708

6.  Natural language processing with dynamic classification improves P300 speller accuracy and bit rate.

Authors:  William Speier; Corey Arnold; Jessica Lu; Ricky K Taira; Nader Pouratian
Journal:  J Neural Eng       Date:  2011-12-12       Impact factor: 5.379

7.  An adaptive P300-based control system.

Authors:  Jing Jin; Brendan Z Allison; Eric W Sellers; Clemens Brunner; Petar Horki; Xingyu Wang; Christa Neuper
Journal:  J Neural Eng       Date:  2011-04-08       Impact factor: 5.379

8.  Targeting an efficient target-to-target interval for P300 speller brain-computer interfaces.

Authors:  Jing Jin; Eric W Sellers; Xingyu Wang
Journal:  Med Biol Eng Comput       Date:  2012-02-18       Impact factor: 2.602

9.  A method for optimizing EEG electrode number and configuration for signal acquisition in P300 speller systems.

Authors:  William Speier; Aniket Deshpande; Nader Pouratian
Journal:  Clin Neurophysiol       Date:  2014-09-28       Impact factor: 3.708

10.  A general P300 brain-computer interface presentation paradigm based on performance guided constraints.

Authors:  George Townsend; Jessica Shanahan; David B Ryan; Eric W Sellers
Journal:  Neurosci Lett       Date:  2012-08-29       Impact factor: 3.046

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