Abstract
Long-term use of computer screens and reduced eye blink rate may lead to a disease known as a dry eye syndrome. As a preventive step, this paper proposes a novel system that monitors eye blink rate continuously using Web camera and alarms the computer user in case if blink rate is reduced less than a certain threshold. The accuracy of the proposed system is 90%. A factorial experiment has been carried out to evaluate the performance of the proposed system under the different conditions. A regression equation which relates accuracy of the system with the affecting parameters has been proposed.
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References
Z. Yan, L. Hu, H. Chen and F. Lu, “Computer Vision Syndrome: A widely spreading but largely unknown epidemic among computer users”, Computers in Human Behavior, vol. 24, no. 5, pp. 2026–2042, 2008.
Crnovrsanin, Tarik, Yang Wang, and Kwan-Liu Ma. “Stimulating a blink: reduction of eye fatigue with visual stimulus.” Proceedings of the 32nd annual ACM conference on Human factors in computing systems. ACM, 2014.
Freudenthaler, Nora, et al. “Characteristics of spontaneous eyeblink activity during video display terminal use in healthy volunteers.” Graefe’s archive for clinical and experimental ophthalmology 241.11 (2003): 914–920.
Schlote, Torsten, Gregor Kadner, and Nora Freudenthaler. “Marked reduction and distinct patterns of eye blinking in patients with moderately dry eyes during video display terminal use.” Graefe’s archive for clinical and experimental ophthalmology 242.4 (2004): 306–312.
Anshel, Jeffrey, ed. Visual ergonomics handbook. CRC Press, 2005.
Pedersen, Simon Just Kjeldgaard. “Circular hough transform.” Aalborg University, Vision, Graphics, and Interactive Systems 123 (2007).
K. Arai and R. Mardiyanto, “Comparative study on blink detection and gaze estimation methods for hci, in particular, gabor lter utilized blink detection method”, in 2011 International Conference on Information Technology: New Generations, 2011, pp. 441–446
T. Soukupova and J.Cech, “Real-Time Eye Blink Detection using Facial Landmarks”, 21st Computer Vision Winter Workshop, Slovenia, 2016.
P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple features,” Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001, pp. I-511–I-518 vol.1.
“Blink and you miss it!”, Ucl.ac.uk. 2017[Online] Available: https://www.ucl.ac.uk/media/library/blinking.
D. Montgomery, Design and analysis of experiments, 5th ed. John Wiley and Sons Inc. New York.
“Minitab Statistical Software - Minitab”, Minitab.com, 2017. [Online]. Available: https://www.minitab.com/products/minitab.
Acknowledgements
We extend our gratitude toward Dr. Mandar Paranjape for explaining the concerns and remedies relating to dry eye syndrome.
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Govardhane, P., Wyawahare, M. (2018). An Eye Blink Detection System for Dry Eye Syndrome and Its Performance Model. In: Perez, G., Tiwari, S., Trivedi, M., Mishra, K. (eds) Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, vol 696. Springer, Singapore. https://doi.org/10.1007/978-981-10-7386-1_41
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DOI: https://doi.org/10.1007/978-981-10-7386-1_41
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