Literature DB >> 21911058

Spelling with non-invasive Brain-Computer Interfaces--current and future trends.

Hubert Cecotti1.   

Abstract

Brain-Computer Interfaces (BCIs) have become a large research field that include challenges mainly in neuroscience, signal processing, machine learning and user interface. A non-invasive BCI can allow the direct communication between humans and computers by analyzing electrical brain activity, recorded at the surface of the scalp with electroencephalography. The main purpose for BCIs is to enable communication for people with severe disabilities. Spelling is one of the first BCI application, it corresponds to the main communication mean for people who are unable to speak. While spelling can be the most basic application it remains a benchmark for communication applications and one challenge in the BCI community for some patients. This paper proposes a review of the current main strategies, and their limitations, for spelling words. It includes recent BCIs based on P300, steady-state visual evoked potentials and motor imagery. By considering some challenges in BCI spellers and virtual keyboards, some pragmatic issues are pointed out to eliminate false hopes about BCI for both disabled and healthy people.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21911058     DOI: 10.1016/j.jphysparis.2011.08.003

Source DB:  PubMed          Journal:  J Physiol Paris        ISSN: 0928-4257


  27 in total

1.  High-speed spelling with a noninvasive brain-computer interface.

Authors:  Xiaogang Chen; Yijun Wang; Masaki Nakanishi; Xiaorong Gao; Tzyy-Ping Jung; Shangkai Gao
Journal:  Proc Natl Acad Sci U S A       Date:  2015-10-19       Impact factor: 11.205

Review 2.  Human visual skills for brain-computer interface use: a tutorial.

Authors:  Melanie Fried-Oken; Michelle Kinsella; Betts Peters; Brandon Eddy; Bruce Wojciechowski
Journal:  Disabil Rehabil Assist Technol       Date:  2020-06-01

3.  Evaluation of feature extraction methods for EEG-based brain-computer interfaces in terms of robustness to slight changes in electrode locations.

Authors:  Sun-Ae Park; Han-Jeong Hwang; Jeong-Hwan Lim; Jong-Ho Choi; Hyun-Kyo Jung; Chang-Hwan Im
Journal:  Med Biol Eng Comput       Date:  2013-01-17       Impact factor: 2.602

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

5.  A novel approach for designing authentication system using a picture based P300 speller.

Authors:  Nikhil Rathi; Rajesh Singla; Sheela Tiwari
Journal:  Cogn Neurodyn       Date:  2021-01-30       Impact factor: 3.473

Review 6.  EEG-EOG based Virtual Keyboard: Toward Hybrid Brain Computer Interface.

Authors:  Sarah M Hosni; Howida A Shedeed; Mai S Mabrouk; Mohamed F Tolba
Journal:  Neuroinformatics       Date:  2019-07

7.  Brain-Computer Interfaces in Neurorecovery and Neurorehabilitation.

Authors:  Michael J Young; David J Lin; Leigh R Hochberg
Journal:  Semin Neurol       Date:  2021-03-19       Impact factor: 3.212

Review 8.  Language model applications to spelling with Brain-Computer Interfaces.

Authors:  Anderson Mora-Cortes; Nikolay V Manyakov; Nikolay Chumerin; Marc M Van Hulle
Journal:  Sensors (Basel)       Date:  2014-03-26       Impact factor: 3.576

Review 9.  Cognitive-motor brain-machine interfaces.

Authors:  Ariel Tankus; Itzhak Fried; Shy Shoham
Journal:  J Physiol Paris       Date:  2013-06-15

Review 10.  Methods of EEG signal features extraction using linear analysis in frequency and time-frequency domains.

Authors:  Amjed S Al-Fahoum; Ausilah A Al-Fraihat
Journal:  ISRN Neurosci       Date:  2014-02-13
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