The DOI matches its Crossref record; 182 of the 189 references it cites were found in a registry or an index.
The Argus® II Retinal Prosthesis System
Abstract
The Argus(®) II Retinal Prosthesis System (Second Sight Medical Products) is the first prosthetic vision device to obtain regulatory approval in both Europe and the USA. As such it has entered the commercial market as a treatment for patients with profound vision loss from end-stage outer retinal disease, predominantly retinitis pigmentosa. To date, over 100 devices have been implanted worldwide, representing the largest group of patients currently treated with visual prostheses. The system works by direct stimulation of the relatively preserved inner retina via epiretinal microelectrodes, thereby replacing the function of the degenerated photoreceptors. Visual information from a glasses-mounted video camera is converted to a pixelated image by an external processor, before being transmitted to the microelectrode array at the macula. Elicited retinal responses are then relayed via the normal optic nerve to the cortex for interpretation. We reviewed the animal and human studies that led to the development of the Argus(®) II device. A sufficiently robust safety profile was demonstrated in the phase I/II clinical trial of 30 patients. Improvement of function in terms of orientation and mobility, target localisation, shape and object recognition, and reading of letters and short unrehearsed words have also been shown. There remains a wide variability in the functional outcomes amongst the patients and the factors contributing to these performance differences are still unclear. Future developments in terms of both software and hardware aimed at improving visual function have been proposed. Further experience in clinical outcomes is being acquired due to increasing implantation.
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In the citing paper
“The Argus II and PRIMA devices were designed to reduce FOV even further, thereby providing improved image resolution through a digital zoom.9,10,65”
From Visual Prostheses in the Era of Artificial Intelligence Technology (2025) · cites this paper as [9]
In the citing paper
“Argus II can restore rudimentary vision of BVI, however, the image information delivered by the implant electrodes is quite limited, the high risks and high costs of invasive treatments have also hindered its widespread application.”
From StereoPilot: A Wearable Target Location System for Blind and Visually Impaired Using Spatial Audio Rendering (2022) · cites this paper as [4]
In the citing paper
“Its successor, the Argus II,9 used 60 electrodes, leading to demonstrably higher visual acuity21 compared to its predecessor”
From Visual Prostheses in the Era of Artificial Intelligence Technology (2025) · cites this paper as [9]
In the citing paper
“Various RCPs have enabled blind individuals to perform simple visual tasks.9”
From Visual Prostheses in the Era of Artificial Intelligence Technology (2025) · cites this paper as [9]
In the citing paper
“By this metric, comparison of visual acuity with the device switched ON and OFF showed improvement only for the PRIMA35 and Argus II9 devices.”
From Visual Prostheses in the Era of Artificial Intelligence Technology (2025) · cites this paper as [9]
In the citing paper
“So far, retinal prostheses have reached marketing approval [23,53,111], and other devices are in preclinical and clinical testing.”
From Advances in visual prostheses: engineering and biological challenges (2022) · cites this paper as [111]
In the citing paper
“The Argus® II [111] was among the first implantable microelectrode arrays manufactured with cleanroom processes to be approved by regulatory agencies.”
From Advances in visual prostheses: engineering and biological challenges (2022) · cites this paper as [111]
In the citing paper
“Most clinical neural interfaces function in a monopolar configuration with a common and distant return ground placed several millimetres away [9-12].”
From Three-dimensional multilayer concentric bipolar electrodes restrict spatial activation in optic nerve stimulation (2022) · cites this paper as [9]
Citations
Cites
Hodgkin, A. L., & Huxley, A. F. (1952) · The Journal of Physiology · doi:10.1113/jphysiol.1952.sp004764 · Cited by 23,191
A model of saliency-based visual attention for rapid scene analysis
Itti, L., Christof Koch, A., & Niebur, E. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.730558 · Cited by 11,289
Wong, W. L., Su, X., Li, X., Cheung, C. M. G., Klein, R., Cheng, C., & Wong, T. Y. (2014) · The Lancet Global Health · doi:10.1016/s2214-109x(13)70145-1 · Cited by 5,545
Hartong, D. T., Berson, E. L., & Dryja, T. P. (2006) · The Lancet · doi:10.1016/s0140-6736(06)69740-7 · Cited by 2,924
Topography of ganglion cells in human retina
Curcio, C. A., & Allen, K. A. (1990) · The Journal of Comparative Neurology · doi:10.1002/cne.903000103 · Cited by 1,849
The development and application of optogenetics
Fenno, L., Yizhar, O., & Deisseroth, K. (2011) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-061010-113817 · Cited by 1,822
Activation of the primary visual cortex by Braille reading in blind subjects
Sadato, N., Pascual-Leone, A., Grafman, J., Ibañez, V., Deiber, M.-P., Dold, G., & Hallett, M. (1996) · Nature · doi:10.1038/380526a0 · Cited by 1,253
Better speech recognition with cochlear implants
Wilson, B. S., Finley, C. C., Lawson, D. T., Wolford, R. D., Eddington, D. K., & Rabinowitz, W. M. (1991) · Nature · doi:10.1038/352236a0 · Cited by 1,211
The sensations produced by electrical stimulation of the visual cortex
Brindley, G. S., & Lewin, W. S. (1968) · The Journal of Physiology · doi:10.1113/jphysiol.1968.sp008519 · Cited by 1,170
Cross-modal plasticity: where and how?
Bavelier, D., & Neville, H. J. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn848 · Cited by 1,040
Flagged first, then by citations
7 of the 189 references couldn’t be matched to a known paper.
Research works printed but not linked: 5
- Brindley, 1964, The number of information channels needed for efficient reading, J. Physiol., 44
- Dagnelie, 2014, (16:30) Electrically elicited ERGs and VEPs in Argus II recipients: a window into signal processing in the degenerated RP retina, Doc. Ophthalmol., 1, 34
- Foerster, 1929, Beiträge zur Pathophysiologie der Sehbahn und der Sehsphäre, J. Psychol. Neurol., 463
- Milam, 1998, Histopathology of the human retina in retinitis pigmentosa, Prog. Retin. Eye Res., 17, 175
- OECD, 2012. Magnetic resonance imaging (MRI) exams, total 2012/2. oecd-ilibrary.org. http://dx.doi.org/10.1787/mri-exam-total-table-2012-2-en. · DOI
Cited by
Sorted by citations
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Villarreal, D. L., Zevallos, E. J. C., Perea, A. M., & Krautschneider, W. H. (2021) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc46164.2021.9629768
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Li, W., Xu, Z., Wang, H., & Wu, T. (2021) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc46164.2021.9630580
Chou, H., Wu, A., Cheng, Y.-C., & Wang, N. (2020) · Retina atlas · doi:10.1007/978-981-15-0414-3_1
Wang, R., Yu, H., & Li, Z. (2018) · Micro/Nano technologies · doi:10.1007/978-981-10-5945-2_41
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Ran, Z., & Sun, H. (2022) · International Conference on Systems and Informatics (ICSAI) · doi:10.1109/icsai57119.2022.10005387
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Gopal, L. (2023) · Indian Journal of Ophthalmology · doi:10.4103/ijo.ijo_1683_23
Lavoie, J., Besrour, M., Lemaire, W., Rouat, J., Fontaine, R., & Plourde, É. (2023) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/acf1a5
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Firsov, M. L. (2024) · Neuroscience and Behavioral Physiology · doi:10.1007/s11055-024-01597-8
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Tso, K.-C., Sunaga, Y., Nakanishi, Y., Terasawa, Y., Haruta, M., Sasagawa, K., & Ohta, J. (2025) · Micromachines · doi:10.3390/mi16050580
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Kim, C., Son, Y., Park, J. W., Kim, M., Roh, H., Lee, S., Lee, B. C., Lee, H., Kang, M. G., Lee, S. H., et al. (2026) · IEEE International Conference on Micro Electro Mechanical Systems (MEMS) · doi:10.1109/mems64181.2026.11419531
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Scialom, E., Lonnqvist, B., Bornet, A., & Herzog, M. H. (2026) · Journal of Neural Engineering · doi:10.1088/1741-2552/ae9227
Fuentes, Á. R., Carrizosa, M. J., Ramos, R., Gil-Simoes, R., & Alén, J. F. (2026) · IEEE Access · doi:10.1109/access.2026.3731112
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Ji, B., Zhang, Z., You, X., Wang, X., Huang, Y., Cao, J., Bai, R., Chen, J., Zhao, H., Chang, H., et al. (2026) · Rare Metals · doi:10.1002/rar2.70619
Ma, Y., Li, Y., Zhang, S., Liang, L., & Li, G. (2026) · Neural Networks · doi:10.1016/j.neunet.2026.109693
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Oh, Y., & Kim, J. (2026) · Electronics · doi:10.3390/electronics15194551
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Shen, W., Chen, M., Peng, Y., Wang, J., Zhong, H., Xie, J., Zhou, Y., Gao, Q., Huang, X., Gou, Z., et al. (2026) · Bioactive Materials · doi:10.1016/j.bioactmat.2026.09.044
Renshaw, K. T., & Pezaris, J. S. (2026) · Oxford University Press eBooks · doi:10.1093/9780197851494.003.0595
Liu, Z., Liu, J., Pang, J., Guo, X., Wang, L., Song, X., Li, H., Chai, X., Gan, H., Gong, S., et al. (2026) · Cognitive Neurodynamics · doi:10.1007/s11571-026-10573-6
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Moure, P., Granley, J., Grani, F., Soo, L., Lozano, A., López-Peco, R., Villamarin-Ortiz, A., Soto-Sanchez, C., Liu, S.-C., Beyeler, M., et al. (2025) · bioRxiv · doi:10.1101/2025.09.24.678361
Metadata
- Authors
- Luo, Y. H.-L., & da Cruz, L.
- Affiliations
- Moorfields Eye Hospital NHS Foundation Trust (GB)
- ORCID
- Luo, Yvonne Hsu-Lin
- Venue
- Progress in Retinal and Eye Research
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 50
- Pages
- 89-107
- ISSN
- 1350-9462 (ISSN-L)
- OpenAlex
- W1778783464
- Cited by
- 351
- References
- 189
- Citations by year
- 2026: 21 · 2025: 36 · 2024: 32 · 2023: 36 · 2022: 38 · 2021: 43 · 2020: 37 · 2019: 36 · 2018: 33 · 2017: 24 · 2016: 14
- FWCI
- 2.82
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Progress in Retinal and Eye Research (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Health Sciences › Medicine › Ophthalmology › Retinal Development and Disorders
- Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
- Keywords
- Argus II, retinal prosthesis, retinitis pigmentosa, photoreceptor degeneration, vision loss, visual prosthesis, orientation and mobility, visual function outcomes, device safety, animal studies, clinical trials
- MeSH terms
- Animals, Blindness, Electrodes, Implanted, Electric Stimulation Therapy, Humans, Prosthesis Design, Retinal Diseases, Visual Acuity, Visual Perception, Visual Prosthesis, Implantable Neurostimulators
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