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A Study on Eye-Blink Detection-Based Communication System by Using K-Nearest Neighbors ClassifierEKIM, G. , IKIZLER, N. , ATASOY, A. |
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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
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. |
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[1] A Novel Approach on Converting Eye Blink Signals in EEG to Speech with Cross Correlation Technique, IKIZLER, N., EKIM, G., ATASOY, A., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 23, 2023.
Digital Object Identifier: 10.4316/AECE.2023.02004 [CrossRef] [Full text]
[2] Design recommendations for voluntary blink interactions based on pressure sensors, Fan, Lin-Han, Huang, Wei-Chi, Shao, Xue-Qi, Niu, Ya-Feng, Advanced Engineering Informatics, ISSN 1474-0346, Issue , 2024.
Digital Object Identifier: 10.1016/j.aei.2024.102489 [CrossRef]
[3] 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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