Literature DB >> 16792301

The Wadsworth BCI Research and Development Program: at home with BCI.

Theresa M Vaughan1, Dennis J McFarland, Gerwin Schalk, William A Sarnacki, Dean J Krusienski, Eric W Sellers, Jonathan R Wolpaw.   

Abstract

The ultimate goal of brain-computer interface (BCI) technology is to provide communication and control capacities to people with severe motor disabilities. BCI research at the Wadsworth Center focuses primarily on noninvasive, electroencephalography (EEG)-based BCI methods. We have shown that people, including those with severe motor disabilities, can learn to use sensorimotor rhythms (SMRs) to move a cursor rapidly and accurately in one or two dimensions. We have also improved P300-based BCI operation. We are now translating this laboratory-proven BCI technology into a system that can be used by severely disabled people in their homes with minimal ongoing technical oversight. To accomplish this, we have: improved our general-purpose BCI software (BCI2000); improved online adaptation and feature translation for SMR-based BCI operation; improved the accuracy and bandwidth of P300-based BCI operation; reduced the complexity of system hardware and software and begun to evaluate home system use in appropriate users. These developments have resulted in prototype systems for every day use in people's homes.

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Year:  2006        PMID: 16792301     DOI: 10.1109/TNSRE.2006.875577

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  65 in total

1.  Control of a visual keyboard using an electrocorticographic brain-computer interface.

Authors:  Dean J Krusienski; Jerry J Shih
Journal:  Neurorehabil Neural Repair       Date:  2010-10-04       Impact factor: 3.919

2.  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

Review 3.  Brain-computer interfaces in medicine.

Authors:  Jerry J Shih; Dean J Krusienski; Jonathan R Wolpaw
Journal:  Mayo Clin Proc       Date:  2012-02-10       Impact factor: 7.616

4.  Single tap identification for fast BCI control.

Authors:  Ian Daly; Slawomir J Nasuto; Kevin Warwick
Journal:  Cogn Neurodyn       Date:  2010-09-01       Impact factor: 5.082

5.  Does the 'P300' speller depend on eye gaze?

Authors:  P Brunner; S Joshi; S Briskin; J R Wolpaw; H Bischof; G Schalk
Journal:  J Neural Eng       Date:  2010-09-21       Impact factor: 5.379

6.  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

7.  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

Review 8.  Advanced neurotechnologies for chronic neural interfaces: new horizons and clinical opportunities.

Authors:  Daryl R Kipke; William Shain; György Buzsáki; E Fetz; Jaimie M Henderson; Jamille F Hetke; Gerwin Schalk
Journal:  J Neurosci       Date:  2008-11-12       Impact factor: 6.167

9.  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

10.  Brain-computer interface (BCI) evaluation in people with amyotrophic lateral sclerosis.

Authors:  Lynn M McCane; Eric W Sellers; Dennis J McFarland; Joseph N Mak; C Steve Carmack; Debra Zeitlin; Jonathan R Wolpaw; Theresa M Vaughan
Journal:  Amyotroph Lateral Scler Frontotemporal Degener       Date:  2014-02-20       Impact factor: 4.092

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