Literature DB >> 32034787

Brain-computer interfaces for amyotrophic lateral sclerosis.

Dennis J McFarland1.   

Abstract

A brain-computer interface (BCI) is a device that detects signals from the brain and transforms them into useful commands. Researchers have developed BCIs that utilize different kinds of brain signals. These different BCI systems have differing characteristics, such as the amount of training required and the degree to which they are or are not invasive. Much of the research on BCIs to date has involved healthy individuals and evaluation of classification algorithms. Some BCIs have been shown to have potential benefit for users with minimal muscular function as a result of amyotrophic lateral sclerosis. However, there are still several challenges that need to be successfully addressed before BCIs can be clinically useful.
© 2020 Wiley Periodicals, Inc.

Entities:  

Keywords:  amyotrophic lateral sclerosis; brain-computer interface; neuroprosthetics

Mesh:

Year:  2020        PMID: 32034787      PMCID: PMC7952029          DOI: 10.1002/mus.26828

Source DB:  PubMed          Journal:  Muscle Nerve        ISSN: 0148-639X            Impact factor:   3.217


  54 in total

1.  Brain-computer interfaces based on the steady-state visual-evoked response.

Authors:  M Middendorf; G McMillan; G Calhoun; K S Jones
Journal:  IEEE Trans Rehabil Eng       Date:  2000-06

2.  To hype, or not to(o) hype. Communication of science is often tarnished by sensationalization, for which both scientists and the media are responsible.

Authors:  Andrea Rinaldi
Journal:  EMBO Rep       Date:  2012-04-02       Impact factor: 8.807

3.  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 4.  Neuropsychology and neuropharmacology of P3a and P3b.

Authors:  John Polich; José R Criado
Journal:  Int J Psychophysiol       Date:  2006-02-28       Impact factor: 2.997

5.  An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method.

Authors:  Guangyu Bin; Xiaorong Gao; Zheng Yan; Bo Hong; Shangkai Gao
Journal:  J Neural Eng       Date:  2009-06-03       Impact factor: 5.379

6.  Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials.

Authors:  L A Farwell; E Donchin
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1988-12

Review 7.  Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation.

Authors:  Bijan Pesaran; Martin Vinck; Gaute T Einevoll; Anton Sirota; Pascal Fries; Markus Siegel; Wilson Truccolo; Charles E Schroeder; Ramesh Srinivasan
Journal:  Nat Neurosci       Date:  2018-06-25       Impact factor: 24.884

Review 8.  BCI in practice.

Authors:  D J McFarland; T M Vaughan
Journal:  Prog Brain Res       Date:  2016-07-15       Impact factor: 2.453

Review 9.  Brain tissue responses to neural implants impact signal sensitivity and intervention strategies.

Authors:  Takashi D Y Kozai; Andrea S Jaquins-Gerstl; Alberto L Vazquez; Adrian C Michael; X Tracy Cui
Journal:  ACS Chem Neurosci       Date:  2015-01-12       Impact factor: 4.418

10.  Stability of a chronic implanted brain-computer interface in late-stage amyotrophic lateral sclerosis.

Authors:  Elmar G M Pels; Erik J Aarnoutse; Sacha Leinders; Zac V Freudenburg; Mariana P Branco; Benny H van der Vijgh; Tom J Snijders; Timothy Denison; Mariska J Vansteensel; Nick F Ramsey
Journal:  Clin Neurophysiol       Date:  2019-07-27       Impact factor: 3.708

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  2 in total

1.  EEG-based vibrotactile evoked brain-computer interfaces system: A systematic review.

Authors:  Xiuyu Huang; Shuang Liang; Zengguang Li; Cynthia Yuen Yi Lai; Kup-Sze Choi
Journal:  PLoS One       Date:  2022-06-03       Impact factor: 3.752

2.  Evaluation of a P300-Based Brain-Machine Interface for a Robotic Hand-Orthosis Control.

Authors:  Jonathan Delijorge; Omar Mendoza-Montoya; Jose L Gordillo; Ricardo Caraza; Hector R Martinez; Javier M Antelis
Journal:  Front Neurosci       Date:  2020-11-27       Impact factor: 4.677

  2 in total

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