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A brain–computer interface for the Dasher alternative text entry system

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Abstract

To investigate whether the alternative text entry system, Dasher, is useful to physically and intellectually disabled students when controlled by a brain–computer interface (BCI) a new software tool was developed to allow subjects to type words onto a computer screen via Dasher using their thoughts. A case study approach was adopted. Subjects were selected based on their suitability for the experiment, and the potential benefit to them of this system, by their head teacher. Subjects entered literacy level-matched phrases onto a computer using QWERTY keyboard, Dasher-mouse and Dasher-BCI. A researcher recorded qualitative and quantitative data, including characters entered per minute and their system preferences. Informed written consent was given for seven subjects to participate (aged 14–19 years, five male, with a range of physical and intellectual disabilities). After a short training period, all subjects had some degree of control over the Dasher-BCI system. With regard to typing speed, Dasher-BCI performed relatively poorly (3.9 ± 1.5 characters per minute), and QWERTY keyboard performed the best (31.9 ± 21.9 characters per minute). Dasher-BCI was the most preferred method. Areas of weakness in Dasher and the BCI hardware were highlighted and suggestions for improvement given. BCI-based text entry is not yet ready to compete with more established methods for students with combined cognitive and physical disabilities. Although underpowered, this study suggests that for people whose predominant disability is physical (cerebral palsy), BCI technology shows great potential as a viable text entry alternative. Suggestions for further research are discussed.

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Acknowledgments

This work has been partially supported by the AEGIS Project (IST-224348), Open Accessibility Everywhere: Groundwork, Infrastructure, Standards.

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Authors and Affiliations

  1. Computing and Technology, Nottingham Trent University, Clifton Campus, Clifton Lane/A453, Nottingham, NG11 8NS, UK

    David J. Brown, Lindsay Evett & Nasser Sherkat

  2. Radiological and Imaging Sciences, Queen’s Medical Centre, University of Nottingham, Room W/B 1441, B Floor West Block, Nottingham, NG7 2UH, UK

    Thomas Welton

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  1. Thomas Welton
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  2. David J. Brown
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  3. Lindsay Evett
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  4. Nasser Sherkat
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Correspondence to David J. Brown.

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Welton, T., Brown, D.J., Evett, L. et al. A brain–computer interface for the Dasher alternative text entry system. Univ Access Inf Soc 15, 77–83 (2016). https://doi.org/10.1007/s10209-014-0375-y

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