Literature DB >> 16186045

Brain-computer interfaces--the key for the conscious brain locked into a paralyzed body.

Andrea Kübler1, Nicola Neumann.   

Abstract

Brain-computer interfaces (BCIs) are systems that allow us to translate in real-time the electrical activity of the brain in commands to control devices. They do not rely on muscular activity and can therefore provide communication and control for those who are severely paralyzed (locked-in) due to injury or disease. It has been shown that locked-in patients are able to achieve EEG-controlled cursor or limb movement and patients have successfully communicated by means of a BCI. Current BCIs differ in how the neural activity of the brain is recorded, how subjects (humans and animals) are trained to produce a specific EEG response, how the signals are translated into device commands, and which application is provided to the user. The present review focuses on approaches to BCIs that process the EEG on-line and provide EEG feedback or feedback of results to the user. We regard online processing and feedback cornerstones for routine application of BCIs in the field. Because training patients in their home environment is effortful and personal and financial resources are limited, only few studies on BCI long-term use for communication with paralyzed patients are available. The need for multidisciplinary research, comprising computer science, engineering, neuroscience, and psychology is now being acknowledged by the BCI community. A standard BCI platform, referred to as BCI2000, has been developed, which allows us to better combine and compare the different BCI approaches of different laboratories. As BCI laboratories now also join to unify their expertise and collaborations are funded, we consider it realistic that within few years we will be able to offer a BCI, which will be easy to operate for patients and caregivers.

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Year:  2005        PMID: 16186045     DOI: 10.1016/S0079-6123(05)50035-9

Source DB:  PubMed          Journal:  Prog Brain Res        ISSN: 0079-6123            Impact factor:   2.453


  19 in total

1.  Towards an independent brain-computer interface using steady state visual evoked potentials.

Authors:  Brendan Z Allison; Dennis J McFarland; Gerwin Schalk; Shi Dong Zheng; Melody Moore Jackson; Jonathan R Wolpaw
Journal:  Clin Neurophysiol       Date:  2008-02       Impact factor: 3.708

2.  Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects.

Authors:  Joseph N Mak; Jonathan R Wolpaw
Journal:  IEEE Rev Biomed Eng       Date:  2009

3.  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

4.  Novel hold-release functionality in a P300 brain-computer interface.

Authors:  R E Alcaide-Aguirre; J E Huggins
Journal:  J Neural Eng       Date:  2014-11-07       Impact factor: 5.379

Review 5.  Cognitive rehabilitation in non-communicative brain-damaged patients.

Authors:  Luigi Trojano; Pasquale Moretta; Autilia Cozzolino; Annamaria Saltalamacchia; Anna Estraneo
Journal:  Funct Neurol       Date:  2011 Jan-Mar

6.  Sniffing enables communication and environmental control for the severely disabled.

Authors:  Anton Plotkin; Lee Sela; Aharon Weissbrod; Roni Kahana; Lior Haviv; Yaara Yeshurun; Nachum Soroker; Noam Sobel
Journal:  Proc Natl Acad Sci U S A       Date:  2010-07-26       Impact factor: 11.205

7.  The influence of psychological state and motivation on brain-computer interface performance in patients with amyotrophic lateral sclerosis - a longitudinal study.

Authors:  Femke Nijboer; Niels Birbaumer; Andrea Kübler
Journal:  Front Neurosci       Date:  2010-07-21       Impact factor: 4.677

8.  Crosstalk disrupts the production of motor imagery brain signals in brain-computer interfaces.

Authors:  Phoebe S-H Neo; Terence Mayne; Xiping Fu; Zhiyi Huang; Elizabeth A Franz
Journal:  Health Inf Sci Syst       Date:  2021-03-13

9.  Prediction of auditory and visual p300 brain-computer interface aptitude.

Authors:  Sebastian Halder; Eva Maria Hammer; Sonja Claudia Kleih; Martin Bogdan; Wolfgang Rosenstiel; Niels Birbaumer; Andrea Kübler
Journal:  PLoS One       Date:  2013-02-14       Impact factor: 3.240

10.  Introduction: Reconsidering Disorders of Consciousness in Light of Neuroscientific Evidence.

Authors:  Ralf J Jox; Katja Kuehlmeyer
Journal:  Neuroethics       Date:  2011-09-23       Impact factor: 1.480

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