Artificial Vision: History and Modern Trends

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Introduction

Thousands of people worldwide are in need of technology that can restore the ability to see. However, despite a significant increase in innovation in the medical field in recent years, there have long been no affordable and effective ways to implement vision prosthetics. In this regard, there is a need to engage advanced technologies designed to help visually impaired or blind people regain the ability to see. The situation is, nonetheless, complicated because, in addition to the eyeballs themselves, the visual cortex of the brain and the nerve pathways that connect the eyes to the brain are involved in the process (Zhang et al., 2019). Due to the emergence of robotic systems as the latest neuroengineering developments, the future of artificial vision has favorable prospects, and special prostheses can become effective tools to restore peoples ability to see.

History of Artificial Vision

Although advanced technological solutions based on the use of robotic self-learning systems have appeared recently, the process of studying the possibilities of correcting vision started a long time ago. In 1823, J. E. Purkinje, the Czech scholar, became interested in the issues of vision and hallucinations, as well as the possibility of artificial stimulation of visual images (da Mota Gomes, 2019). It was he who first described visual flashes phosphenes, which he received during an experiment with a battery by passing an electric current through his head and describing his visual experience (da Mota Gomes, 2019). One hundred thirty years later, in 1956, J. I. Tassiker patented the first retinal implant that did not give any useful vision but showed that it was possible to artificially induce visual signals (Allen, 2021). However, ocular prostheses have been slowed down for a long time due to technological limitations.

It took a long time before any real developments appeared, which could give vision that a person could use. According to Farnum and Pelled (2020), in 2019, there were approximately 50 active projects in the world, which focused on vision prosthetics. Bionic implants have proved the greatest clinical effectiveness, resembling robotic information processing systems by the type of their structure and functioning. Therefore, these devices may be called the future of ophthalmic neurosurgery.

Modern Trends in Bionic Implants

The fundamental technologies by which bionic vision implants are produced are algorithms that help stimulate individual areas of the eye system. The modern variety of these devices is due to the distinctive approaches to production, as well as to the purpose since different vision problems are addressed. The modern market of bionic implants allows selecting optimal systems that correspond to individual characteristics and perform specific functions.

Retinal Nanotubes

One of the simplest but least efficient technologies is equipping the eye system with retinal nanotubes. In 2018, a group of scholars from China conducted an experiment on mice, during which they proposed the use of nanotubes instead of non-functioning retinal photoreceptors (Wu et al., 2021). The advantage of this project is the small size of these devices. However, each of the nanotubes can only stimulate a few retinal cells, which makes their use not the most convenient.

Biopixels

Biopixels are microparticles that perform a function similar to real cells. They have a sheath made of a lipid layer in which photosensitive proteins are embedded (Sarkar & Bagh, 2022). They are affected by light quanta, and as in real cells, their electric potential changes, thus arising an electric signal (Sarkar & Bagh, 2022). This technology has not yet become widespread, but its development is continuous.

Perovskite Artificial Retina

The main developments associated with this technology are aimed at stimulating all layers of living cells. With the help of perovskite artificial retina technology, scholars are trying to provide the ability to not only receive light sensations but also to distinguish color by modeling the signal (Yang et al., 2020). This can be performed in such a way that the signal is perceived by the brain as having a certain color, as a result of which a person is able to view a particular object naturally.

Photovoltaic Membrane

This material is a small film coated with a layer of a chemical. This substance has the property of absorbing light and converting it into an electrical signal (Taherimakhsousi et al., 2021). The membrane is placed on a spherical base so that it can be conveniently placed on the fundus (Taherimakhsousi et al., 2021). Such a mechanism for prosthetics is complex, but it can be applied in large quantities if it becomes more accessible.

Semiconductor Polymer

The technology of introducing a semiconductor polymer solution under the retina is a form of special chemical prosthetics. With the help of this material, the light is fixed and transformed into electrical signals, sending impulses to the brain and giving a person the ability to see (Maya-Vetencourt et al., 2020). All of the considered implantation systems can be effective, but some devices that work on the principle of artificial vision are implanted directly into the brain, thus being more complex structures.

Cortical Implantation System

Cortical prostheses are a special subgroup of visual neuroprostheses that are installed directly into the brain. They are able to induce visual perceptions in blind people through direct electrical stimulation of the occipital cortex that is responsible for image recognition (Foroushani et al., 2018). This approach may be the only available treatment for blindness caused by glaucoma, end-stage retinitis pigmentosa, optic nerve atrophy, retinal and optic nerve injury, and other problems (Foroushani et al., 2018). In recent years, neuroengineers have made significant progress in creating this intracortical visual neuroprosthesis that can restore limited but useful vision.

Cortical prostheses may vary depending on specific criteria and purpose. For instance, as Foroushani et al. (2018) note, a prerequisite for installing one of such implants is the patients visual experience. This means it can only be used for people with a developed visual cortex who were born sighted and have lost their sight. These devices can also be intracortical and consist of groups of miniature wireless implantable stimulator grids that transmit image information directly to the human brain (Foroushani et al., 2018). The development of technology allows improving modern developments, and bionic robotic devices can become integral tools in the lives of thousands of people.

Conclusion

People in dire need of vision restoration can count on modern robotic devices developed due to the latest neural engineering advancements. Work in this direction has been going on for dozens of years, and to date, a wide range of solutions has been presented, which can perform different functions and meet individual needs. In addition to bionic prostheses, cortical implantation systems are applied, which are complex and efficient algorithms. The industry is progressive, and machine intelligence, augmented by robotic tools, may help solve the problem of low or no vision in the future.

References

Allen, P. J. (2021). Retinal prostheses: Where to from here? Clinical & Experimental Ophthalmology, 49(5), 418-429.

da Mota Gomes, M. (2019). Jan Evangelista Purkinje, a brilliant, multifaceted Czech biologist: Nerve tissue. Revista Brasileira de Neurologia, 55(4), 13-17. Web.

Farnum, A., & Pelled, G. (2020). New vision for visual prostheses. Frontiers in Neuroscience, 14(36), 1-11.

Foroushani, A. N., Pack, C. C., & Sawan, M. (2018). Cortical visual prostheses: From microstimulation to functional percept. Journal of Neural Engineering, 15(2), 021005.

Maya-Vetencourt, J. F., Manfredi, G., Mete, M., Colombo, E., Bramini, M., Di Marco, S., Shmal, D., Mantero, G., Dipalo, M., Rocchi, A., DiFrancesco, M. L., Papaleo, E. D., Russo, A., Barsotti, J., Eleftheriou, C., Di Maria, F., Cossu, V., Piazza, F., Emionite, L., & & Benfenati, F. (2020). Subretinally injected semiconducting polymer nanoparticles rescue vision in a rat model of retinal dystrophy. Nature Nanotechnology, 15(8), 698-708.

Sarkar, K., & Bagh, S. (2022). Synthetic gene circuits for higher-order information processing. New Frontiers and Applications of Synthetic Biology, 373-395.

Taherimakhsousi, N., Fievez, M., MacLeod, B. P., Booker, E. P., Fayard, E., Matheron, M., Manceau, M., Cros, S., Berson, S., & Berlinguette, C. P. (2021). A machine vision tool for facilitating the optimization of large-area perovskite photovoltaics. NPJ Computational Materials, 7(1), 1-10.

Wu, N., Wan, S., Su, S., Huang, H., Dou, G., & Sun, L. (2021). Electrode materials for brain-machine interface: A review. InfoMat, 3(11), 1174-1194.

Yang, X., Xiong, Z., Chen, Y., Ren, Y., Zhou, L., Li, H., Zhou, Y., Pan, F., & Han, S. T. (2020). A self-powered artificial retina perception system for image preprocessing based on photovoltaic devices and memristive arrays. Nano Energy, 78, 105246.

Zhang, H. J., Mi, X. S., & So, K. F. (2019). Normal tension glaucoma: From the brain to the eye or the inverse? Neural Regeneration Research, 14(11), 1845-1850. Web.

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