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A Novel Dictionary-Driven Mental Spelling Application Based on Code-Modulated Visual Evoked Potentials

Faculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, 47533 Kleve, Germany
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Computers 2019, 8(2), 33; https://doi.org/10.3390/computers8020033
Received: 9 April 2019 / Revised: 25 April 2019 / Accepted: 26 April 2019 / Published: 30 April 2019
(This article belongs to the Special Issue Computer Technologies for Human-Centered Cyber World)
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Abstract

Brain–computer interfaces (BCIs) based on code-modulated visual evoked potentials (c-VEPs) typically utilize a synchronous approach to identify targets (i.e., after preset time periods the system produces command outputs). Hence, users have only a limited amount of time to fixate a desired target. This hinders the usage of more complex interfaces, as these require the BCI to distinguish between intentional and unintentional fixations. In this article, we investigate a dynamic sliding window mechanism as well as the implementation of software-based stimulus synchronization to enable the threshold-based target identification for the c-VEP paradigm. To further improve the usability of the system, an ensemble-based classification strategy was investigated. In addition, a software-based approach for stimulus on-set determination is proposed, which allows for an easier setup of the system, as it reduces additional hardware dependencies. The methods were tested with an eight-target spelling application utilizing an n-gram word prediction model. The performance of eighteen participants without disabilities was tested; all participants completed word- and sentence spelling tasks using the c-VEP BCI with a mean information transfer rate (ITR) of 75.7 and 57.8 bpm, respectively. View Full-Text
Keywords: brain–computer interface (BCI); electroencephalogram (EEG); visual evoked potentials (VEP); code-modulated visual evoked potentials (c-VEP) brain–computer interface (BCI); electroencephalogram (EEG); visual evoked potentials (VEP); code-modulated visual evoked potentials (c-VEP)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Gembler, F.; Volosyak, I. A Novel Dictionary-Driven Mental Spelling Application Based on Code-Modulated Visual Evoked Potentials. Computers 2019, 8, 33.

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