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Brain Sci. 2018, 8(7), 126; https://doi.org/10.3390/brainsci8070126

A 20-Questions-Based Binary Spelling Interface for Communication Systems

1
Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, 72076 Tübingen, Germany
2
Wyss-Center for Bio- and Neuro-Engineering, 1202 Geneva, Switzerland
*
Author to whom correspondence should be addressed.
Received: 11 June 2018 / Revised: 28 June 2018 / Accepted: 30 June 2018 / Published: 2 July 2018
(This article belongs to the Special Issue Brain-Computer Interfaces for Human Augmentation)
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Abstract

Brain computer interfaces (BCIs) enables people with motor impairments to communicate using their brain signals by selecting letters and words from a screen. However, these spellers do not work for people in a complete locked-in state (CLIS). For these patients, a near infrared spectroscopy-based BCI has been developed, allowing them to reply to “yes”/”no” questions with a classification accuracy of 70%. Because of the non-optimal accuracy, a usual character-based speller for selecting letters or words cannot be used. In this paper, a novel spelling interface based on the popular 20-questions-game has been presented, which will allow patients to communicate using only “yes”/”no” answers, even in the presence of poor classification accuracy. The communication system is based on an artificial neural network (ANN) that estimates a statement thought by the patient asking less than 20 questions. The ANN has been tested in a web-based version with healthy participants and in offline simulations. Both results indicate that the proposed system can estimate a patient’s imagined sentence with an accuracy that varies from 40%, in the case of a “yes”/”no” classification accuracy of 70%, and up to 100% in the best case. These results show that the proposed spelling interface could allow patients in CLIS to express their own thoughts, instead of only answer to “yes”/”no” questions. View Full-Text
Keywords: brain computer interface; complete locked-in state; communication; Artificial Neural Network; 20-questions-game brain computer interface; complete locked-in state; communication; Artificial Neural Network; 20-questions-game
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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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Tonin, A.; Birbaumer, N.; Chaudhary, U. A 20-Questions-Based Binary Spelling Interface for Communication Systems. Brain Sci. 2018, 8, 126.

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