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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  1/2023 - 8

A Study on Eye-Blink Detection-Based Communication System by Using K-Nearest Neighbors Classifier

EKIM, G. See more information about EKIM, G. on SCOPUS See more information about EKIM, G. on IEEExplore See more information about EKIM, G. on Web of Science, IKIZLER, N. See more information about  IKIZLER, N. on SCOPUS See more information about  IKIZLER, N. on SCOPUS See more information about IKIZLER, N. on Web of Science, ATASOY, A. See more information about ATASOY, A. on SCOPUS See more information about ATASOY, A. on SCOPUS See more information about ATASOY, A. on Web of Science
 
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Download PDF pdficon (1,252 KB) | Citation | Downloads: 681 | Views: 793

Author keywords
assistive technology, biomedical communication, biomedical signal processing, electroencephalography, machine learning

References keywords
brain(9), communication(7), interface(6), writing(5), system(5), efficient(5), typing(4), time(4), text(4), systems(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2023-02-28
Volume 23, Issue 1, Year 2023, On page(s): 71 - 78
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2023.01008
Web of Science Accession Number: 000937345700008
SCOPUS ID: 85150264613

Abstract
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Full text preview
There are 450 thousand patients in the world who is diagnosed Amyotrophic Lateral Sclerosis. These patients lose control of all the muscles in their body except the eye movements. The purpose of the studies in this research area is to design a system, which the patients can express the basic needs, works with high accuracy, which all patients can afford financially, with minimal discomfort to person. The aim of the developed system is to analyze the eye-blinks made with binary coding and convert them into sound. First, eye-blink signals coded with binary number sequence is obtained with NeuroSky MindWave Mobile device. These coded signals are given as an input to the designed system. In the eye-blink analysis section, the location and number of eye-blinks are determined. Then, the eye-blinks containing coded information in the input signal are classified using the K-Nearest Neighbors algorithm, and the class of the eye-blink is determined. Finally, the letters corresponding to the code of the eye-blink sequence are obtained and the resulting word is vocalized. With its low cost and high accuracy, this system causes minimal discomfort to the patient and has a simple structure.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [Web of Science Times Cited 253]


[2] A. Kaya, A. Dik, Z. Tulek, N. Alankaya, A. Ozakgul, P. Unalan, H. A. Idrisoglu, "Home care project for patients with Amyotrophic Lateral Sclerosis (ALS): "It's not enough to live, it's also to keep alive" required," National Neurology Congress, Antalya, 2015

[3] A. Kaya, F. Ozcan, "Communication with patients with Amyotrophic Lateral Sclerosis (ALS) and current technologies." The Journal of Turkish Family Physician, 8.2: 43-48, 2017.
[CrossRef]


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[CrossRef]


[7] A. Amcalar, M. Cetin, "A brain-computer interface system for online spelling", IEEE 18th Signal Processing and Communication Applications Congress, Diyarbakir, 196-199, 2010.
[CrossRef]


[8] F. Akram, H. Seung Moo, K. Tae-Seong, "An efficient word typing P300-BCI system using a modified T9 interface and random forest classifier," Computers in Biology and Medicine 56, 30-36, 2015.
[CrossRef] [Web of Science Times Cited 66]


[9] Z. Oralhan, "The effect of interstitial time and stimulus structure on performance in P300 based brain computer interface systems", Duzce University Journal of Science and Technology, 7.3: 1834-1846, 2019.
[CrossRef]


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[CrossRef]


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[13] A. B. Usakli, S. Gurkan, "Design of a novel efficient human-computer interface: An electrooculogram based virtual keyboard," IEEE Transactions on Instrumentation and Measurement, 59.8: 2099-2108, 2009.
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[14] C. Zhang, R. Yao, J. Cai," Efficient eye typing with 9-direction gaze estimation," Multimedia Tools, and Applications, 77.15: 19679-19696, 2018.
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[15] H. Ozbek Ulkutas, "Development of computer-based eye-writing system by using EOG," M.Sc. Thesis, Department of Biomedical Engineering, Baskent University, Ankara, Turkey, 2015.

[16] M. Porta, M. Turina, "Eye-S: a full-screen input modality for pure eye-based communication," In Proceedings of the 2008 Symposium on Eye Tracking Research & Applications, 27-34, 2008.
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[18] J. O. Wobbrock, J. Rubinstein, M. Sawyer, A. T. Duchowski, "Not typing but writing: Eye-based text entry using letter-like gestures," In Proceedings of the Conference on Communications by Gaze Interaction (COGAIN, pp. 61-64, September 2007

[19] K. R. Lee, W. D. Chang, S. Kim, C. H. Im, "Real-time "eye-writing" recognition using electrooculogram," IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(1), 37-48, 2016.
[CrossRef] [Web of Science Times Cited 47]


[20] F. Fang, T. Shinozaki, "Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems," PloS one, 13(2), 2018, e0192684.
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[22] A. F. Reyes, E. C. Camacho, M. Armando, J. M. Calderón, "LSTM based brain-machine interface tool for text generation through eyes blinking detection," In 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC) (pp. 1-6). IEEE, January 2021.
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[24] G. Ekim, A. Atasoy, N. Ikizler, "A new approach for eye-blink to speech conversion by dynamic time warping," Traitement Du Signal, Vol:38, No:2, pp 369-377, April 2021.
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[CrossRef]


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[28] P. Thanh Noi, M. Kappas, "Comparison of random forest, K-Nearest Neighbor, and support vector machine classifiers for land cover classification using sentinel-2 imagery", Sensors, 18.1, 18, 2017.
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References Weight

Web of Science® Citations for all references: 3,658 TCR
SCOPUS® Citations for all references: 0

Web of Science® Average Citations per reference: 131 ACR
SCOPUS® Average Citations per reference: 0

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-03-26 01:33 in 115 seconds.




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Stefan cel Mare University of Suceava, Romania


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