Literature DB >> 32301143

30+ years of P300 brain-computer interfaces.

Brendan Z Allison1, Andrea Kübler2, Jing Jin3.   

Abstract

Brain-computer interfaces (BCIs) directly measure brain activity with no physical movement and translate the neural signals into messages. BCIs that employ the P300 event-related brain potential often have used the visual modality. The end user is presented with flashing stimuli that indicate selections for communication, control, or both. Counting each flash that corresponds to a specific target selection while ignoring other flashes will elicit P300s to only the target selection. P300 BCIs also have been implemented using auditory or tactile stimuli. P300 BCIs have been used with a variety of applications for severely disabled end users in their homes without frequent expert support. P300 BCI research and development has made substantial progress, but challenges remain before these tools can become practical devices for impaired patients and perhaps healthy people.
© 2020 Society for Psychophysiological Research.

Entities:  

Keywords:  BCI; EEG; ERP; P300; brain-computer interface

Mesh:

Year:  2020        PMID: 32301143     DOI: 10.1111/psyp.13569

Source DB:  PubMed          Journal:  Psychophysiology        ISSN: 0048-5772            Impact factor:   4.016


  7 in total

1.  Usability of a Hybrid System Combining P300-Based Brain-Computer Interface and Commercial Assistive Technologies to Enhance Communication in People With Multiple Sclerosis.

Authors:  Angela Riccio; Francesca Schettini; Valentina Galiotta; Enrico Giraldi; Maria Grazia Grasso; Febo Cincotti; Donatella Mattia
Journal:  Front Hum Neurosci       Date:  2022-05-26       Impact factor: 3.473

Review 2.  Summary of over Fifty Years with Brain-Computer Interfaces-A Review.

Authors:  Aleksandra Kawala-Sterniuk; Natalia Browarska; Amir Al-Bakri; Mariusz Pelc; Jaroslaw Zygarlicki; Michaela Sidikova; Radek Martinek; Edward Jacek Gorzelanczyk
Journal:  Brain Sci       Date:  2021-01-03

3.  Effect of Distracting Background Speech in an Auditory Brain-Computer Interface.

Authors:  Álvaro Fernández-Rodríguez; Ricardo Ron-Angevin; Ernesto J Sanz-Arigita; Antoine Parize; Juliette Esquirol; Alban Perrier; Simon Laur; Jean-Marc André; Véronique Lespinet-Najib; Liliana Garcia
Journal:  Brain Sci       Date:  2021-01-01

4.  A P300 Brain-Computer Interface With a Reduced Visual Field.

Authors:  Luiza Kirasirova; Vladimir Bulanov; Alexei Ossadtchi; Alexander Kolsanov; Vasily Pyatin; Mikhail Lebedev
Journal:  Front Neurosci       Date:  2020-12-03       Impact factor: 4.677

5.  Exploring the Representations of Individual Entities in the Brain Combining EEG and Distributional Semantics.

Authors:  Andrea Bruera; Massimo Poesio
Journal:  Front Artif Intell       Date:  2022-02-23

6.  How brain-computer interface technology may improve the diagnosis of the disorders of consciousness: A comparative study.

Authors:  Rossella Spataro; Yiyan Xu; Ren Xu; Giorgio Mandalà; Brendan Z Allison; Rupert Ortner; Alexander Heilinger; Vincenzo La Bella; Christoph Guger
Journal:  Front Neurosci       Date:  2022-08-11       Impact factor: 5.152

7.  A novel EEG decoding method for a facial-expression-based BCI system using the combined convolutional neural network and genetic algorithm.

Authors:  Rui Li; Di Liu; Zhijun Li; Jinli Liu; Jincao Zhou; Weiping Liu; Bo Liu; Weiping Fu; Ahmad Bala Alhassan
Journal:  Front Neurosci       Date:  2022-09-13       Impact factor: 5.152

  7 in total

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