Literature DB >> 18989104

Brain-computer interface in paralysis.

Niels Birbaumer1, Ander Ramos Murguialday, Leonardo Cohen.   

Abstract

PURPOSE OF REVIEW: Communication with patients suffering from locked-in syndrome and other forms of paralysis is an unsolved challenge. Movement restoration for patients with chronic stroke or other brain damage also remains a therapeutic problem and available treatments do not offer significant improvements. This review considers recent research in brain-computer interfaces (BCIs) as promising solutions to these challenges. RECENT
FINDINGS: Experimentation with nonhuman primates suggests that intentional goal directed movements of the upper limbs can be reconstructed and transmitted to external manipulandum or robotic devices controlled from a relatively small number of microelectrodes implanted into movement-relevant brain areas after some training, opening the door for the development of BCI or brain-machine interfaces in humans. Although noninvasive BCIs using electroencephalographic recordings or event-related-brain-potentials in healthy individuals and patients with amyotrophic lateral sclerosis or stroke can transmit up to 80 bits/min of information, the use of BCIs - invasive or noninvasive - in severely or totally paralyzed patients has met some unforeseen difficulties.
SUMMARY: Invasive and noninvasive BCIs using recordings from nerve cells, large neuronal pools such as electrocorticogram and electroencephalography, or blood flow based measures such as functional magnetic resonance imaging and near-infrared spectroscopy show potential for communication in locked-in syndrome and movement restoration in chronic stroke, but controlled phase III clinical trials with larger populations of severely disturbed patients are urgently needed.

Entities:  

Mesh:

Year:  2008        PMID: 18989104     DOI: 10.1097/WCO.0b013e328315ee2d

Source DB:  PubMed          Journal:  Curr Opin Neurol        ISSN: 1350-7540            Impact factor:   5.710


  61 in total

1.  Automatic feature selection of motor imagery EEG signals using differential evolution and learning automata.

Authors:  Saugat Bhattacharyya; Abhronil Sengupta; Tathagatha Chakraborti; Amit Konar; D N Tibarewala
Journal:  Med Biol Eng Comput       Date:  2013-10-29       Impact factor: 2.602

2.  Brain oscillatory signatures of motor tasks.

Authors:  Ander Ramos-Murguialday; Niels Birbaumer
Journal:  J Neurophysiol       Date:  2015-03-25       Impact factor: 2.714

3.  New horizons in brain-computer interface research.

Authors:  Eric W Sellers
Journal:  Clin Neurophysiol       Date:  2012-08-16       Impact factor: 3.708

Review 4.  Real-time fMRI neurofeedback: progress and challenges.

Authors:  J Sulzer; S Haller; F Scharnowski; N Weiskopf; N Birbaumer; M L Blefari; A B Bruehl; L G Cohen; R C DeCharms; R Gassert; R Goebel; U Herwig; S LaConte; D Linden; A Luft; E Seifritz; R Sitaram
Journal:  Neuroimage       Date:  2013-03-27       Impact factor: 6.556

5.  Experimental Set Up of P300 Based Brain Computer Interface Using a Bioamplifier and BCI2000 System for Patients with Spinal Cord Injury.

Authors:  Hyeongseok Jeon; Dong Ah Shin
Journal:  Korean J Spine       Date:  2015-09-30

Review 6.  A review of organic and inorganic biomaterials for neural interfaces.

Authors:  Pouria Fattahi; Guang Yang; Gloria Kim; Mohammad Reza Abidian
Journal:  Adv Mater       Date:  2014-03-26       Impact factor: 30.849

Review 7.  Brain-computer interfaces for communication and rehabilitation.

Authors:  Ujwal Chaudhary; Niels Birbaumer; Ander Ramos-Murguialday
Journal:  Nat Rev Neurol       Date:  2016-08-19       Impact factor: 42.937

8.  Decoding covert motivations of free riding and cooperation from multi-feature pattern analysis of EEG signals.

Authors:  Dongil Chung; Kyongsik Yun; Jaeseung Jeong
Journal:  Soc Cogn Affect Neurosci       Date:  2015-02-16       Impact factor: 3.436

9.  Recognition of handwriting from electromyography.

Authors:  Michael Linderman; Mikhail A Lebedev; Joseph S Erlichman
Journal:  PLoS One       Date:  2009-08-26       Impact factor: 3.240

10.  Grand challenges of brain computer interfaces in the years to come.

Authors:  Eilon Vaadia; Niels Birbaumer
Journal:  Front Neurosci       Date:  2009-09-15       Impact factor: 4.677

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.