Gerçek Zamanlı Sanal Klavye için Elektrookülografig Sinyal Toplama ve İşleme

Yıl 2024, Cilt: 5 Sayı: 2, 66 - 75, 20.12.2024

Leila Barour , Ayşe Nur Ay Gül

https://doi.org/10.58769/joinssr.1499482

Öz

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.

Anahtar Kelimeler

EOG, ALS, Virtual Keyboard, Recorded Message.

Electrooculography Signal Acquisition and Processing for Real-Time Virtual Keyboard

Öz

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.

Anahtar Kelimeler

EOG, ALS, Virtual Keyboard, Recorded Message.

Kaynakça

• [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.
• [10] International Engineering, “KL-730_10603,” Scribd.
• [11] M. Trikha, A. Bhandari and T. Gandhi, "Automatic Electrooculogram Classification for Microcontroller Based Interface Design," 2007 IEEE Systems and Information Engineering Design Symposium, Charlottesville, VA, USA, 2007, pp. 1-6, doi: 10.1109/SIEDS.2007.4373994.
• [12] M. Merino, O. Rivera, I. Gómez, A. Molina and E. Dorronzoro, "A Method of EOG Signal Processing to Detect the Direction of Eye Movements," 2010 First International Conference on Sensor Device Technologies and Applications, Venice, Italy, 2010, pp. 100-105, doi: 10.1109/SENSORDEVICES.2010.25.
• [13] H. S. Dhillon, R. Singla, N. S. Rekhi and R. Jha, "EOG and EMG based virtual keyboard: A brain-computer interface," 2009 2nd IEEE International Conference on Computer Science and Information Technology, Beijing, China, 2009, pp. 259-262, doi: 10.1109/ICCSIT.2009.5234951.
• [14] S. S. S. Teja, S. S. Embrandiri, N. Chandrachoodan and Ramasubba Reddy M., "EOG based virtual keyboard," 2015 41st Annual Northeast Biomedical Engineering Conference (NEBEC), Troy, NY, USA, 2015, pp. 1-2, doi: 10.1109/NEBEC.2015.7117201.
• [15] E. Donchin, K. M. Spencer and R. Wijesinghe, "The mental prosthesis: assessing the speed of a P300-based brain-computer interface," in IEEE Transactions on Rehabilitation Engineering, vol. 8, no. 2, pp. 174-179, June 2000, doi: 10.1109/86.847808.
• [16] Anjaliagarwal, “GitHub - anjaliagarwal8/EOG-Keyboard: EOG(Electrooculogram) based virtual keyboard can assist people with motor neuron disease to communicate effectively.,” GitHub.