The application of computer vision to visual prosthesis
- PMID: 34318520
- DOI: 10.1111/aor.14022
The application of computer vision to visual prosthesis
Abstract
A visual prosthesis is an auxiliary device for patients with blinding diseases that cannot be treated with conventional surgery or drugs. It converts captured images into corresponding electrical stimulation patterns, according to which phosphenes are generated through the action of internal electrodes on the visual pathway to form visual perception. However, due to some restrictions such as the few implantable electrodes that the biological tissue can accommodate, the induced perception is far from ideal. Therefore, an important issue in visual prosthesis research is how to detect and present useful information in low-resolution prosthetic vision to improve the visual function of the wearer. In recent years, with the development and broad application of computer vision methods, researchers have investigated the possibility of their utilization in visual prostheses by simulating prosthetic visual percepts. Through the optimization of visual perception by image processing, the efficiency of visual prosthesis devices can be further improved to better meet the needs of prosthesis wearers. In this article, recent works on prosthetic vision centering on implementing computer vision methods are reviewed. Differences, strengths, and weaknesses of the mentioned methods are discussed. The development directions of optimizing prosthetic vision and improving methods of visual perception are analyzed.
Keywords: computer vision; image processing; machine learning; simulated prosthetic vision; visual prosthesis.
© 2021 International Center for Artificial Organs and Transplantation and Wiley Periodicals LLC.
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References
REFERENCES
-
- World Health Organization. WHO launches first World report on vision; c2020. Available from. https://www.who.int/news-room/detail/08-10-2019-who-launches-first-world...
-
- Buchs G, Heimler B, Kerem M, Maidenbaum S, Braun L, Amedi A. Virtual self-training of a sensory substitution device for blind individuals. In: 2019 International Conference on Virtual Rehabilitation (ICVR). Tel Aviv, Israel: IEEE; 2019. 1-2.
-
- Barnes N. The role of computer vision in prosthetic vision. Image Vis Comput. 2012;30:478-9.
-
- Yan Y, Chai XY, Chen Y, Zhou CQ, Ren QS, Li LM. Research progress of visual prosthesis. Sheng Li Xue Bao. 2016 Oct 25;68:628-36. Chinese.
-
- Beauchamp MS, Oswalt D, Sun P, Foster BL, Magnotti JF, Niketeghad S, et al. Dynamic stimulation of visual cortex produces form vision in sighted and blind humans. Cell. 2020;181:774-83.e5. https://doi.org/10.1016/j.cell.2020.04.033
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