Literature DB >> 16792304

DASHER--an efficient writing system for brain-computer interfaces?

Sebastian A Wills1, David J C MacKay.   

Abstract

DASHER is a human-computer interface for entering text using continuous or discrete gestures. Through its use of an internal language model, DASHER efficiently converts bits received from the user into text, and has been shown to be a competitive alternative to existing text-entry methods in situations where an ordinary keyboard cannot be used. We propose that DASHER would be well-matched to the low bit-rate, noisy output obtained from brain-computer interfaces (BCIs), and discuss the issues surrounding the use of DASHER with BCI systems.

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Year:  2006        PMID: 16792304     DOI: 10.1109/TNSRE.2006.875573

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  11 in total

1.  Recursive Bayesian Coding for BCIs.

Authors:  Matt Higger; Fernando Quivira; Murat Akcakaya; Mohammad Moghadamfalahi; Hooman Nezamfar; Mujdat Cetin; Deniz Erdogmus
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2016-07-13       Impact factor: 3.802

Review 2.  Brain-Computer Interfaces for Augmentative and Alternative Communication: A Tutorial.

Authors:  Jonathan S Brumberg; Kevin M Pitt; Alana Mantie-Kozlowski; Jeremy D Burnison
Journal:  Am J Speech Lang Pathol       Date:  2018-02-06       Impact factor: 2.408

3.  Efficient human-machine control with asymmetric marginal reliability input devices.

Authors:  John H Williamson; Melissa Quek; Iulia Popescu; Andrew Ramsay; Roderick Murray-Smith
Journal:  PLoS One       Date:  2020-06-01       Impact factor: 3.240

4.  Neural Point-and-Click Communication by a Person With Incomplete Locked-In Syndrome.

Authors:  Daniel Bacher; Beata Jarosiewicz; Nicolas Y Masse; Sergey D Stavisky; John D Simeral; Katherine Newell; Erin M Oakley; Sydney S Cash; Gerhard Friehs; Leigh R Hochberg
Journal:  Neurorehabil Neural Repair       Date:  2014-11-10       Impact factor: 3.919

5.  Mental workload during brain-computer interface training.

Authors:  Elizabeth A Felton; Justin C Williams; Gregg C Vanderheiden; Robert G Radwin
Journal:  Ergonomics       Date:  2012-04-16       Impact factor: 2.778

6.  The Berlin Brain-Computer Interface: Non-Medical Uses of BCI Technology.

Authors:  Benjamin Blankertz; Michael Tangermann; Carmen Vidaurre; Siamac Fazli; Claudia Sannelli; Stefan Haufe; Cecilia Maeder; Lenny Ramsey; Irene Sturm; Gabriel Curio; Klaus-Robert Müller
Journal:  Front Neurosci       Date:  2010-12-08       Impact factor: 4.677

7.  Combining Brain-Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges.

Authors:  J D R Millán; R Rupp; G R Müller-Putz; R Murray-Smith; C Giugliemma; M Tangermann; C Vidaurre; F Cincotti; A Kübler; R Leeb; C Neuper; K-R Müller; D Mattia
Journal:  Front Neurosci       Date:  2010-09-07       Impact factor: 4.677

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

9.  A Multifunctional Brain-Computer Interface Intended for Home Use: An Evaluation with Healthy Participants and Potential End Users with Dry and Gel-Based Electrodes.

Authors:  Ivo Käthner; Sebastian Halder; Christoph Hintermüller; Arnau Espinosa; Christoph Guger; Felip Miralles; Eloisa Vargiu; Stefan Dauwalder; Xavier Rafael-Palou; Marc Solà; Jean M Daly; Elaine Armstrong; Suzanne Martin; Andrea Kübler
Journal:  Front Neurosci       Date:  2017-05-22       Impact factor: 4.677

10.  Towards user-friendly spelling with an auditory brain-computer interface: the CharStreamer paradigm.

Authors:  Johannes Höhne; Michael Tangermann
Journal:  PLoS One       Date:  2014-06-02       Impact factor: 3.240

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