Literature DB >> 10896194

Brain-computer interface research at the Wadsworth Center.

J R Wolpaw1, D J McFarland, T M Vaughan.   

Abstract

Studies at the Wadsworth Center over the past 14 years have shown that people with or without motor disabilities can learn to control the amplitude of mu or beta rhythms in electroencephalographic (EEG) activity recorded from the scalp over sensorimotor cortex and can use that control to move a cursor on a computer screen in one or two dimensions. This EEG-based brain-computer interface (BCI) could provide a new augmentative communication technology for those who are totally paralyzed or have other severe motor impairments. Present research focuses on improving the speed and accuracy of BCI communication.

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Year:  2000        PMID: 10896194     DOI: 10.1109/86.847823

Source DB:  PubMed          Journal:  IEEE Trans Rehabil Eng        ISSN: 1063-6528


  28 in total

1.  Predictors of successful self control during brain-computer communication.

Authors:  N Neumann; N Birbaumer
Journal:  J Neurol Neurosurg Psychiatry       Date:  2003-08       Impact factor: 10.154

2.  Robust extraction of P300 using constrained ICA for BCI applications.

Authors:  Ozair Idris Khan; Faisal Farooq; Faraz Akram; Mun-Taek Choi; Seung Moo Han; Tae-Seong Kim
Journal:  Med Biol Eng Comput       Date:  2012-01-17       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.  Electro-encephalogram based brain-computer interface: improved performance by mental practice and concentration skills.

Authors:  Babak Mahmoudi; Abbas Erfanian
Journal:  Med Biol Eng Comput       Date:  2006-10-07       Impact factor: 2.602

6.  A comparison approach toward finding the best feature and classifier in cue-based BCI.

Authors:  R Boostani; B Graimann; M H Moradi; G Pfurtscheller
Journal:  Med Biol Eng Comput       Date:  2007-02-23       Impact factor: 2.602

7.  A semi-supervised support vector machine approach for parameter setting in motor imagery-based brain computer interfaces.

Authors:  Jinyi Long; Yuanqing Li; Zhuliang Yu
Journal:  Cogn Neurodyn       Date:  2010-06-08       Impact factor: 5.082

Review 8.  Brain-computer interfaces using sensorimotor rhythms: current state and future perspectives.

Authors:  Han Yuan; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2014-05       Impact factor: 4.538

9.  Real-time two-dimensional asynchronous control of a computer cursor with a single subdural electrode.

Authors:  César Márquez-Chin; Milos R Popovic; Egor Sanin; Robert Chen; Andres M Lozano
Journal:  J Spinal Cord Med       Date:  2012-09       Impact factor: 1.985

10.  An MEG-based brain-computer interface (BCI).

Authors:  Jürgen Mellinger; Gerwin Schalk; Christoph Braun; Hubert Preissl; Wolfgang Rosenstiel; Niels Birbaumer; Andrea Kübler
Journal:  Neuroimage       Date:  2007-03-27       Impact factor: 6.556

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