EN
TR
Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard
Abstract
In situations of disease or trauma, there may be inability to communicate with others through means such as speech or typing. Eye movement tends to be one of the last remaining active muscle capabilities for people with neurodegenerative disorders, such as amyotrophic lateral sclerosis (ALS) also known as Lou Gehrig's disease and for people that are suffering from paralysis and for security silence may be obligation or for privacy or easier communicate without using hands. For that, there is a need for eye movement-based systems to enable communication. The aim of this study is to control keyboard using EOG signals which are obtained from cornea-retinal standing potential that exists between the front and the back of the human eye. It can be extracted by placing electrodes around the eye which can pick up these signals. The result was a written message which exact the wanted letters repeated for the time pause. This can be further improved by adding blinking movement so adding blinking detection algorithms to it to choose the specific letters only.
Keywords
References
- [1] C. Keskinoğlu and A. Aydin, “EOG – Based Computer Control System for People with Mobility Limitations,” Europan Journal of Science and Technology, Jun. 2021, doi: 10.31590/ejosat.948124. [ 2] A. N. A. Gul, M. Sahin, T. Kandis, K. Kavrak and Z. Oner, "Robotic Arm Control Using Machine Learning-Based EOG Signal Classifier," 2023 Medical Technologies Congress (TIPTEKNO), Famagusta, Cyprus, 2023, pp. 1-4, doi: 10.1109/TIPTEKNO59875.2023.10359205.
- [3] N. Barbara, T. A. Camilleri, and K. P. Camilleri, “EOG-based eye movement detection and gaze estimation for an asynchronous virtual keyboard,” Biomedical Signal Processing and Control, vol. 47, pp. 159–167, Jan. 2019, doi: 10.1016/j.bspc.2018.07.005.
- [4] A. B. Usakli and S. Gurkan, “Design of a novel efficient Human–Computer interface: an electrooculagram based virtual keyboard,” IEEE Transactions on Instrumentation and Measurement, vol. 59, no. 8, pp. 2099–2108, Aug. 2010, doi: 10.1109/tim.2009.2030923.
- [5] A. Anandika, P. D. Laksono, M. S. A. B. Suhaimi, J. Muguro, and M. I. Rusydi, “Enhancing interface efficiency: Adaptive virtual keyboard minimizing keystrokes in Electrooculography-Based control,” Jurnal Nasional Teknik Elektro, pp. 64–72, Dec. 2023, doi: 10.25077/jnte.v12n3.1160.2023.
- [6] F. Fang and T. Shinozaki, “Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems,” PLoS ONE, vol. 13, no. 2, p. e0192684, Feb. 2018, doi: 10.1371/journal.pone.0192684.
- [7] W. Tangsuksant, C. Aekmunkhongpaisal, P. Cambua, T. Charoenpong, and T. Chanwimalueang, “Directional eye movement detection system for virtual keyboard controller,” 2012. https://www.semanticscholar.org/paper/Directional-eye-movement-detection-system-for-Tangsuksant-Aekmunkhongpaisal/3bc91bde3c0d8101a2745a17de2f518c7927f2f5
- [8] Z. Lv, X.-P. Wu, M. Li, and D. Zhang, “A novel eye movement detection algorithm for EOG driven human computer interface,” Pattern Recognition Letters, vol. 31, no. 9, pp. 1041–1047, Jul. 2010, doi: 10.1016/j.patrec.2009.12.017.
- [9] J. Heo, H. Yoon, and K. Park, “A novel wearable forehead EOG measurement system for human computer interfaces,” Sensors, vol. 17, no. 7, p. 1485, Jun. 2017, doi: 10.3390/s17071485.
Details
Primary Language
English
Subjects
Biomedical Engineering (Other), Electronic Sensors
Journal Section
Research Article
Publication Date
December 20, 2024
Submission Date
June 11, 2024
Acceptance Date
September 1, 2024
Published in Issue
Year 2024 Volume: 5 Number: 2
APA
Barour, L., & Ay Gül, A. N. (2024). Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard. Journal of Smart Systems Research, 5(2), 66-75. https://doi.org/10.58769/joinssr.1499482
AMA
1.Barour L, Ay Gül AN. Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard. JoinSSR. 2024;5(2):66-75. doi:10.58769/joinssr.1499482
Chicago
Barour, Leila, and Ayşe Nur Ay Gül. 2024. “Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard”. Journal of Smart Systems Research 5 (2): 66-75. https://doi.org/10.58769/joinssr.1499482.
EndNote
Barour L, Ay Gül AN (December 1, 2024) Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard. Journal of Smart Systems Research 5 2 66–75.
IEEE
[1]L. Barour and A. N. Ay Gül, “Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard”, JoinSSR, vol. 5, no. 2, pp. 66–75, Dec. 2024, doi: 10.58769/joinssr.1499482.
ISNAD
Barour, Leila - Ay Gül, Ayşe Nur. “Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard”. Journal of Smart Systems Research 5/2 (December 1, 2024): 66-75. https://doi.org/10.58769/joinssr.1499482.
JAMA
1.Barour L, Ay Gül AN. Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard. JoinSSR. 2024;5:66–75.
MLA
Barour, Leila, and Ayşe Nur Ay Gül. “Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard”. Journal of Smart Systems Research, vol. 5, no. 2, Dec. 2024, pp. 66-75, doi:10.58769/joinssr.1499482.
Vancouver
1.Leila Barour, Ayşe Nur Ay Gül. Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard. JoinSSR. 2024 Dec. 1;5(2):66-75. doi:10.58769/joinssr.1499482