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      Spelling is Just a Click Away – A User-Centered Brain–Computer Interface Including Auto-Calibration and Predictive Text Entry

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          Abstract

          Brain–computer interfaces (BCI) based on event-related potentials (ERP) allow for selection of characters from a visually presented character-matrix and thus provide a communication channel for users with neurodegenerative disease. Although they have been topic of research for more than 20 years and were multiply proven to be a reliable communication method, BCIs are almost exclusively used in experimental settings, handled by qualified experts. This study investigates if ERP–BCIs can be handled independently by laymen without expert support, which is inevitable for establishing BCIs in end-user’s daily life situations. Furthermore we compared the classic character-by-character text entry against a predictive text entry (PTE) that directly incorporates predictive text into the character-matrix. N = 19 BCI novices handled a user-centered ERP–BCI application on their own without expert support. The software individually adjusted classifier weights and control parameters in the background, invisible to the user (auto-calibration). All participants were able to operate the software on their own and to twice correctly spell a sentence with the auto-calibrated classifier (once with PTE, once without). Our PTE increased spelling speed and, importantly, did not reduce accuracy. In sum, this study demonstrates feasibility of auto-calibrating ERP–BCI use, independently by laymen and the strong benefit of integrating predictive text directly into the character-matrix.

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          Most cited references32

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

          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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            A review of classification algorithms for EEG-based brain–computer interfaces

            In this paper we review classification algorithms used to design brain-computer interface (BCI) systems based on electroencephalography (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.
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              The P300 wave of the human event-related potential.

              T Picton (1992)
              The P300 wave is a positive deflection in the human event-related potential. It is most commonly elicited in an "oddball" paradigm when a subject detects an occasional "target" stimulus in a regular train of standard stimuli. The P300 wave only occurs if the subject is actively engaged in the task of detecting the targets. Its amplitude varies with the improbability of the targets. Its latency varies with the difficulty of discriminating the target stimulus from the standard stimuli. A typical peak latency when a young adult subject makes a simple discrimination is 300 ms. In patients with decreased cognitive ability, the P300 is smaller and later than in age-matched normal subjects. The intracerebral origin of the P300 wave is not known and its role in cognition not clearly understood. The P300 may have multiple intracerebral generators, with the hippocampus and various association areas of the neocortex all contributing to the scalp-recorded potential. The P300 wave may represent the transfer of information to consciousness, a process that involves many different regions of the brain.
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                Author and article information

                Journal
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Research Foundation
                1662-4548
                1662-453X
                23 May 2012
                2012
                : 6
                : 72
                Affiliations
                [1] 1simpleDepartment for Psychology I, Institute for Psychology, University of Würzburg Würzburg, Germany
                Author notes

                Edited by: Emanuel Donchin, University of South Florida, USA

                Reviewed by: Alireza Mousavi, Brunel University, UK; Michal Lavidor, Bar Ilan University, Israel

                *Correspondence: Tobias Kaufmann, Department for Psychology I, University of Würzburg, Marcusstr. 9-11, 97070 Würzburg, Germany. e-mail: tobias.kaufmann@ 123456uni-wuerzburg.de

                This article was submitted to Frontiers in Neuroprosthetics, a specialty of Frontiers in Neuroscience.

                Article
                10.3389/fnins.2012.00072
                3400942
                22833713
                1cf85a1a-7558-4ee3-977e-74a21ea26b1a
                Copyright © 2012 Kaufmann, Völker, Gunesch and Kübler.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.

                History
                : 14 February 2012
                : 30 April 2012
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 40, Pages: 10, Words: 6420
                Categories
                Neuroscience
                Original Research

                Neurosciences
                p300-speller,erp-bci,user-centered,brain–computer interface,predictive text entry,auto-calibration,assisitve technology,event-related potentials

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