EyeMo: A Solution for Individuals with Disabilities to Use a Computer Through Eye Movements

Year 2024, Volume: 12 Issue: 1, 224 - 232, 25.03.2024

Hakan Yılmaz Mehmet Özdem

https://doi.org/10.29109/gujsc.1404305

Abstract

The maintenance of an upright posture and the execution of desired movements by individuals necessitate the seamless and harmonious functioning of the muscular and skeletal systems. Neuromuscular diseases, spinal cord injuries, and related conditions can adversely impact individuals' motor functions, leading to a loss of muscle strength and, in severe cases, paralysis. Such health challenges may result in social isolation and detachment from one's social life. This study is focused on the development of a computer control application utilizing eye movements to aid users in navigating and interacting with computers. The system utilizes a lightweight eyeglass frame and a mini-USB camera to accurately capture images of the user's pupil. Pupil detection is achieved through a combination of traditional image processing and deep learning techniques, ensuring high accuracy under diverse conditions. Users have the ability to interactively calibrate the application to accommodate varying screen sizes, thereby enhancing system responsiveness. The user interface incorporates functionalities such as left-click, right-click, double-click, and scrolling, empowering users to perform tasks ranging from internet browsing to video watching.
After the development of the application, a request for research permission was submitted to the local institution to allow volunteers to test the application, adhering to ethical standards. Following the approval of ethical clearance, the application was made available for use by volunteers, and feedback was systematically collected. Volunteers generally reported that the application was beneficial, indicating its potential use by disadvantaged individuals. The upcoming versions of the application have the potential for integration with smart home systems. Additionally, the developed application can be used in games and for educational purposes.

Keywords

Pupil detection, eye tracking, disabilities individual, image processing.

References

• [1] P. S. G. Stein, Ed., Neurons, networks, and motor behavior, 1. paperback ed. in Computational neuroscience. Cambridge, Mass. London: MIT Press, 1999.
• [2] J. M. Shefner, ‘Strength Testing in Motor Neuron Diseases’, Neurotherapeutics, vol. 14, no. 1, pp. 154–160, Jan. 2017, doi: 10.1007/s13311-016-0472-0.
• [3] T. M. McMillan, M. P. Barnes, and C. D. Ward, Handbook of Neurological Rehabilitation, 2nd ed. Hove: Taylor and Francis, 2014.
• [4] J. C. Van Den Bergen et al., ‘Dystrophin levels and clinical severity in Becker muscular dystrophy patients’, Journal of Neurology, Neurosurgery & Psychiatry, vol. 85, no. 7, pp. 747–753, Jul. 2014, doi: 10.1136/jnnp-2013-306350.
• [5] E. Tiryaki and H. A. Horak, ‘ALS and Other Motor Neuron Diseases’, CONTINUUM: Lifelong Learning in Neurology, vol. 20, pp. 1185–1207, Oct. 2014, doi: 10.1212/01.CON.0000455886.14298.a4.
• [6] K. Nas, L. Yazmalar, V. Şah, A. Aydın, and K. Öneş, ‘Rehabilitation of spinal cord injuries’, World J Orthop, vol. 6, no. 1, pp. 8–16, Jan. 2015, doi: 10.5312/wjo.v6.i1.8.
• [7] B. Bora Başara, İ. Soytutan Çağlar, A. Aygün, T. A. Özdemir, and B. Kulali, Eds., T.C. Sağlık Bakanlığı Sağlık İstatistikleri Yıllığı. Türkiye Cumhuriyeti Sağlık Bakanlığı Sağlık Bilgi Sistemleri Genel Müdürlüğü, 2023.
• [8] E. A. Arslan and A. Cansu, ‘Distrofinopati Hastalarının Demografik, Klinik ve Genetik Özellikleri: Tek Merkez Üçüncü Basamak Deneyimi’, Acibadem Univ Saglik Bilim Derg, no. 2, Art. no. 2, Jun. 2020.
• [9] M. Tütüncü, ‘Motor Nöron Hastalıklarında Epidemiyoloji’, Turkiye Klinikleri J Neurol-Special Topics, vol. 16, no. 1, pp. 9–14, 2023.
• [10] J. Park, J.-E. Kim, and T.-J. Song, ‘The Global Burden of Motor Neuron Disease: An Analysis of the 2019 Global Burden of Disease Study’, Front. Neurol., vol. 13, p. 864339, Apr. 2022, doi: 10.3389/fneur.2022.864339.
• [11] C.-S. Hwang, H.-H. Weng, L.-F. Wang, C.-H. Tsai, and H.-T. Chang, ‘An Eye-Tracking Assistive Device Improves the Quality of Life for ALS Patients and Reduces the Caregivers’ Burden’, Journal of Motor Behavior, vol. 46, no. 4, pp. 233–238, Jul. 2014, doi: 10.1080/00222895.2014.891970.
• [12] H. Yilmaz, P. H. Aydin, and M. Turan, ‘Gözle Bilgisayar Kullanımı İçin Prototip Geliştirilmesi’, Computer Science, Sep. 2021, doi: 10.53070/bbd.989215.
• [13] J. C. Licklider and R. W. Taylor, ‘The computer as a communication device’, Science and technology, vol. 76, no. 2, pp. 1–3, 1968.
• [14] A. Kaya and F. Özcan, ‘Communication with the patiens of Amyotrophic Lateral Sclerosis and current technology’, tjtfp, vol. 8, no. 2, pp. 43–48, Jun. 2017, doi: 10.15511/tjtfp.17.00243.
• [15] D. R. Beukelman, S. Fager, L. Ball, and A. Dietz, ‘AAC for adults with acquired neurological conditions: A review’, Augmentative and Alternative Communication, vol. 23, no. 3, pp. 230–242, Jan. 2007, doi: 10.1080/07434610701553668.
• [16] R. Spataro, M. Ciriacono, C. Manno, and V. L. Bella, ‘The eye-tracking computer device for communication in amyotrophic lateral sclerosis’, Acta Neurologica Scandinavica, vol. 130, no. 1, pp. 40–45, 2014, doi: https://doi.org/10.1111/ane.12214.
• [17] D. Beukelman, S. Fager, and A. Nordness, ‘Communication Support for People with ALS’, Neurology Research International, vol. 2011, pp. 1–6, 2011, doi: 10.1155/2011/714693.
• [18] P. Majaranta et al., Gaze Interaction and Applications of Eye Tracking: Advances in Assistive Technologies. IGI Global, 2012. doi: 10.4018/978-1-61350-098-9.
• [19] N. A. Atasoy, A. C. Avusog, and F. Atasoy, ‘Real-time motorized electrical hospital bed control with eye-gaze tracking’, p. 12.
• [20] A. Murata, ‘Eye‐gaze input versus mouse: Cursor control as a function of age’, International Journal of Human-Computer Interaction, vol. 21, no. 1, pp. 1–14, Sep. 2006, doi: 10.1080/10447310609526168.
• [21] H. Drewes, ‘Eye Gaze Tracking for Human Computer Interaction’, Ludwig-Maximilians-Universität München, 2010. doi: 10.5282/EDOC.11591.
• [22] O. Tuisku, V. Surakka, V. Rantanen, T. Vanhala, and J. Lekkala, ‘Text Entry by Gazing and Smiling’, Advances in Human-Computer Interaction, vol. 2013, pp. 1–13, 2013, doi: 10.1155/2013/218084.
• [23] C. Sanchez, V. Costa, R. Garcia-Carmona, E. Urendes, J. Tejedor, and R. Raya, ‘Evaluation of Child–Computer Interaction Using Fitts’ Law: A Comparison between a Standard Computer Mouse and a Head Mouse’, Sensors, vol. 21, no. 11, p. 3826, May 2021, doi: 10.3390/s21113826.
• [24] C. A. M. Pereira, R. B. Neto, A. C. Reynaldo, M. C. De Miranda Luzo, and R. P. Oliveira, ‘Development and Evaluation of a Head-Controlled Human-Computer Interface with Mouse-Like Functions for Physically Disabled Users’, Clinics, vol. 64, no. 10, pp. 975–981, Oct. 2009, doi: 10.1590/S1807-59322009001000007.
• [25] R. H. Abiyev and M. Arslan, ‘Head mouse control system for people with disabilities’, Expert Systems, vol. 37, no. 1, p. e12398, Feb. 2020, doi: 10.1111/exsy.12398.
• [26] Y. Fu and T. S. Huang, ‘hMouse: Head Tracking Driven Virtual Computer Mouse’, in 2007 IEEE Workshop on Applications of Computer Vision (WACV ’07), Austin, TX: IEEE, Feb. 2007, pp. 30–30. doi: 10.1109/WACV.2007.29.
• [27] S. Eivazi, T. Santini, A. Keshavarzi, T. Kübler, and A. Mazzei, ‘Improving real-time CNN-based pupil detection through domain-specific data augmentation’, in Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications, Denver Colorado: ACM, Jun. 2019, pp. 1–6. doi: 10.1145/3314111.3319914.
• [28] F. J. Vera-Olmos, E. Pardo, H. Melero, and N. Malpica, ‘DeepEye: Deep convolutional network for pupil detection in real environments’, ICA, vol. 26, no. 1, pp. 85–95, Dec. 2018, doi: 10.3233/ICA-180584.
• [29] W. Fuhl, T. Santini, G. Kasneci, and E. Kasneci, ‘PupilNet: Convolutional Neural Networks for Robust Pupil Detection’, 2016, doi: 10.48550/ARXIV.1601.04902.
• [30] C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna, ‘Rethinking the Inception Architecture for Computer Vision’, 2015, doi: 10.48550/ARXIV.1512.00567.