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      Alternative communication systems for people with severe motor disabilities: a survey

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          Abstract

          We have now sufficient evidence that using electrical biosignals in the field of Alternative and Augmented Communication is feasible. Additionally, they are particularly suitable in the case of people with severe motor impairment, e.g. people with high-level spinal cord injury or with locked-up syndrome. Developing solutions for them implies that we find ways to use sensors that fit the user's needs and limitations, which in turn impacts the specifications of the system translating the user's intentions into commands. After devising solutions for a given user or profile, the system should be evaluated with an appropriate method, allowing a comparison with other solutions. This paper submits a review of the way three bioelectrical signals - electromyographic, electrooculographic and electroencephalographic - have been utilised in alternative communication with patients suffering severe motor restrictions. It also offers a comparative study of the various methods applied to measure the performance of AAC systems.

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          BCI2000: a general-purpose brain-computer interface (BCI) system.

          Gerwin Schalk, Dennis J McFarland, Thilo Hinterberger … (2004)
          Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods, processing algorithms, output formats, and operating protocols. However, the typical BCI system is designed specifically for one particular BCI method and is, therefore, not suited to the systematic studies that are essential for continued progress. In response to this problem, we have developed a documented general-purpose BCI research and development platform called BCI2000. BCI2000 can incorporate alone or in combination any brain signals, signal processing methods, output devices, and operating protocols. This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BC12000 system is based upon and gives examples of successful BCI implementations using this system. To date, we have used BCI2000 to create BCI systems for a variety of brain signals, processing methods, and applications. The data show that these systems function well in online operation and that BCI2000 satisfies the stringent real-time requirements of BCI systems. By substantially reducing labor and cost, BCI2000 facilitates the implementation of different BCI systems and other psychophysiological experiments. It is available with full documentation and free of charge for research or educational purposes and is currently being used in a variety of studies by many research groups.
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            Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials

            L.A. Farwell, E Donchin (1988)
            This paper describes the development and testing of a system whereby one can communicate through a computer by using the P300 component of the event-related brain potential (ERP). Such a system may be used as a communication aid by individuals who cannot use any motor system for communication (e.g., 'locked-in' patients). The 26 letters of the alphabet, together with several other symbols and commands, are displayed on a computer screen which serves as the keyboard or prosthetic device. The subject focuses attention successively on the characters he wishes to communicate. The computer detects the chosen character on-line and in real time. This detection is achieved by repeatedly flashing rows and columns of the matrix. When the elements containing the chosen character are flashed, a P300 is elicited, and it is this P300 that is detected by the computer. We report an analysis of the operating characteristics of the system when used with normal volunteers, who took part in 2 experimental sessions. In the first session (the pilot study/training session) subjects attempted to spell a word and convey it to a voice synthesizer for production. In the second session (the analysis of the operating characteristics of the system) subjects were required simply to attend to individual letters of a word for a specific number of trials while data were recorded for off-line analysis. The analyses suggest that this communication channel can be operated accurately at the rate of 0.20 bits/sec. In other words, under the conditions we used, subjects can communicate 12.0 bits, or 2.3 characters, per min.
            Article 0 comments Cited 384 times – based on 0 reviews     Review now
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              Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans.

              Jonathan Wolpaw, Dennis J McFarland (2004)
              Brain-computer interfaces (BCIs) can provide communication and control to people who are totally paralyzed. BCIs can use noninvasive or invasive methods for recording the brain signals that convey the user's commands. Whereas noninvasive BCIs are already in use for simple applications, it has been widely assumed that only invasive BCIs, which use electrodes implanted in the brain, can provide multidimensional movement control of a robotic arm or a neuroprosthesis. We now show that a noninvasive BCI that uses scalp-recorded electroencephalographic activity and an adaptive algorithm can provide humans, including people with spinal cord injuries, with multidimensional point-to-point movement control that falls within the range of that reported with invasive methods in monkeys. In movement time, precision, and accuracy, the results are comparable to those with invasive BCIs. The adaptive algorithm used in this noninvasive BCI identifies and focuses on the electroencephalographic features that the person is best able to control and encourages further improvement in that control. The results suggest that people with severe motor disabilities could use brain signals to operate a robotic arm or a neuroprosthesis without needing to have electrodes implanted in their brains.
              Article 0 comments Cited 285 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Biomed Eng Online
                Title: BioMedical Engineering OnLine
                Publisher: BioMed Central
                ISSN (Electronic): 1475-925X
                Publication date Collection: 2011
                Publication date (Electronic): 20 April 2011
                Volume: 10
                Page: 31
                Affiliations
                [1 ]Laboratoire d'Automatique humaine et de Sciences Comportementales, Université de Metz, Bâtiment ISEA, 7 rue Marconi, 57070 METZ Technopôle, France
                [2 ]School of Electrical and Computing Engineering, Federal University of Goiás, Av. Universitária, n. 1488 - Quadra 86 - Bloco A, 74605-010, Goiânia, GO, Brazil
                [3 ]Faculty of Electrical Engineering, Biomedical Engineering Laboratory (BioLab), Federal University of Uberlandia, Campus Santa Monica, 38.408-100 Uberlandia, MG, Brazil
                Article
                Publisher ID: 1475-925X-10-31
                DOI: 10.1186/1475-925X-10-31
                PMC ID: 3103465
                PubMed ID: 21507236
                SO-VID: 37ff763e-a277-4bae-9d4c-1b1cad7783d2
                Copyright © Copyright ©2011 Pinheiro et al; licensee BioMed Central Ltd.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 29 June 2010
                Date accepted : 20 April 2011
                Categories
                Subject: Review

                ScienceOpen disciplines: Biomedical engineering
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                ScienceOpen disciplines: Biomedical engineering

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