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A Novel Approach on Converting Eye Blink Signals in EEG to Speech with Cross Correlation TechniqueIKIZLER, N.   , EKIM, G. , ATASOY, A. |
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Author keywords
assistive technology, biomedical communication, biomedical signal processing, electroencephalography, cross correlation
References keywords
interface(16), communication(16), brain(15), system(11), tracking(8), technology(7), systems(7), blink(7), time(6), information(6)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2023-05-31
Volume 23, Issue 2, Year 2023, On page(s): 29 - 38
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2023.02004
Web of Science Accession Number: 001009953400004
SCOPUS ID: 85164324896
Abstract
Today, there are many patients with Amyotrophic Lateral Sclerosis or paralysis who are unable to perform any body movements other than eye movements. A system has been developed to facilitate communication between patients and their surroundings. This system utilizes binary coded expressions obtained through single and double eye blinks performed by the patients, which are then vocalized. The locations of the eye blinks are determined by analyzing the signals obtained from the patient using a wireless NeuroSky MindWave single-channel EEG device. The windowing process is performed at predetermined intervals to determine whether the blink within these windows was a single or double blink, by using the Cross Correlation method. The system is completed by converting the expressions corresponding to the binary codes to speech and has provided results with a very high degree of accuracy. |
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[1] Call with eyes: A robust interface based on ANN to assist people with locked-in syndrome, Beltrán-Vargas, Roberto Alan, Sandoval-Espino, Jorge Arturo, Marbán-Salgado, José Antonio, Licea-Rodriguez, Jacob, Palillero-Sandoval, Omar, Escobedo-Alatorre, J Jesús, SoftwareX, ISSN 2352-7110, Issue , 2024.
Digital Object Identifier: 10.1016/j.softx.2024.101883 [CrossRef]
[2] EEG Based Communication System by Using Artificial Neural Networks, Ekim, Gunes, Ikizler, Nuri, Atasoy, Ayten, 2023 Medical Technologies Congress (TIPTEKNO), ISBN 979-8-3503-2896-7, 2023.
Digital Object Identifier: 10.1109/TIPTEKNO59875.2023.10359177 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
