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A predictive speller controlled by a brain-computer interface based on motor imagery

Published: 25 October 2012 Publication History

Abstract

Persons suffering from motor disorders have limited possibilities for communicating and normally require assistive technologies to fulfill this primary need. Promising means of providing basic communication abilities to subjects affected by severe motor impairments include brain-computer interfaces (BCIs), that is, systems that directly translate brain signals into device commands, bypassing any muscle or nerve mediation. To date, the use of BCIs for effective verbal communication is yet an open issue, primarily due to the low rates of information transfer that can be achieved with this technology. Still, performance of BCI spelling applications could be considerably improved by a smart user interface design and by the adoption of natural language processing (NLP) techniques for text prediction. The objective of this work is to suggest an approach and a user interface for BCI spelling applications combining state-of-the-art BCI and NLP techniques to maximize the overall communication rate of the system. The BCI paradigm adopted is motor imagery, that is, when the subject imagines moving a certain part of the body, he/she produces modifications to specific brain rhythms that are detected in real-time through an electroencephalogram and translated into commands for a spelling application. By maximizing the overall communication rate, our approach is twofold: on one hand, we maximize the information transfer rate from the control signal, on the other hand, we optimize the way this information is employed for the purpose of verbal communication. The achieved results are satisfactory and comparable with the latest works reported in literature on motor-imagery BCI spellers. For the three subjects tested, we obtained a spelling rate of respectively 3 char/min, 2.7 char/min, and 2 char/min.

Supplementary Material

a20-dalbis-apndx.pdf (dalbis.zip)
Supplemental movie, appendix, image and software files for, A predictive speller controlled by a brain-computer interface based on motor imagery.

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    Published In

    cover image ACM Transactions on Computer-Human Interaction
    ACM Transactions on Computer-Human Interaction  Volume 19, Issue 3
    October 2012
    209 pages
    ISSN:1073-0516
    EISSN:1557-7325
    DOI:10.1145/2362364
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 25 October 2012
    Accepted: 01 April 2012
    Revised: 01 September 2011
    Received: 01 November 2010
    Published in TOCHI Volume 19, Issue 3

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    Author Tags

    1. BCI
    2. BMI
    3. NLP
    4. brain-computer interface
    5. speller
    6. text prediction

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