Abstract
Retinal prosthesis systems have undergone significant advances in the past quarter century, resulting in the development of several different novel surgical and engineering approaches. Encouraging results have demonstrated partial visual restoration, with improvement in both coarse objective function and performance of everyday tasks. To date, four systems have received marketing approval for use in Europe or the United States, with numerous others undergoing preclinical and clinical evaluation, reflecting the established safety profile of these devices for chronic implantation. This progress represents the first notion that the field of visual restorative medicine could offer blind patients a hope of real and measurable benefit. However, there are numerous complex engineering and biophysical obstacles still to be overcome, to reconcile the gap that remains between artificial and natural vision. Current developments in the form of enhanced image processing algorithms and data transfer approaches, combined with emerging nanofabrication and conductive polymerization techniques, herald an exciting and innovative future for retinal prosthetics. This review provides an update of retinal prosthetic systems currently undergoing development and clinical trials while also addressing future challenges in the field, such as the assessment of functional outcomes in ultra-low vision and strategies for tackling existing hardware and software constraints.
Keywords: microelectrode, photovoltaic, retinal prosthesis, tissue electronics
Introduction
Hereditary retinal diseases, such as retinitis pigmentosa (RP), or degenerative conditions, including age-related macular degeneration (AMD), can lead to loss of photoreceptor (PR) cells, while generally preserving the inner retinal neurons.1,2 In both cases, there are no current treatment options to reverse the profound visual disability associated with advanced disease. RP is thought to affect around 1/4000 people, and in the United Kingdom, inherited retinal disorders are the commonest reason for certification of blindness in working age people.1,3 The estimated prevalence of geographic atrophy is 1.3% of the general UK population and is forecast to rise with the aging population.4
Recent advances in biotechnology have seen the first in-human trials, and in some cases market approval, of stem cell and gene therapies as well as retinal prostheses.5–10 In terms of ocular and especially retinal treatments, it is retinal prostheses that have had the longest period of development to date.
The first notion of electrical-induced visual percepts or ‘phosphenes’ came about in 1755, when Charles Le Roy applied an electrical current across the ocular surface of a blind patient, who reported seeing flashes of light. Later, in 1929, Foerster11 showed that acute external stimulation of the exposed occipital pole could also elicit subjective phosphenes. In 1968, Brindley and Lewin exploited this phenomenon, using an 80-electrode chronically implanted prosthesis to deliver electrical stimulation to the visual cortex and elicit phosphenes that coordinated with the retinotopic map previously described by Holmes in war-wounded patients.12,13 Shortly afterward, Potts and Inoue14 demonstrated that electrical current across the globe of patients with RP could elicit subjective phosphenes and evoke recordable responses from electrodes placed over the occipital scalp.
In the 1980s, advances in materials and microelectronics fabrication, combined with developments in vitreo-retinal surgery, allowed for the emergence of the field of retinal prosthetics. Since then, several groups have formed around the world, with a range of approaches, but with the common goal of developing a device that can restore some form of vision in the context of profound vision loss. As well as retinal prostheses, other approaches include intracranial stimulation devices, which act on the cortical or thalamic visual pathways and optic nerve prostheses.15 Another very different approach is to couple visual input to another functioning sensory system. Devices including lingual stimulation from a visual input, harnessing touch on the tongue, as well as auditory-based systems have been described.16
In this review, we have focused on those devices that are intended to deliver direct stimulation to the residual retinal neurons and, in particular, those that have progressed to the stage of human trials. It is not intended as an exhaustive list, but instead an update, and an overview of future directions.
Epiretinal prostheses
Epiretinal prosthesis systems are placed on the surface of the neurosensory retina, adjacent to the nerve fiber and ganglion cell layers. Surgical delivery of these devices is usually transvitreal through a pars plana sclerotomy. The microelectrode array is secured to the retinal surface with a tack. The advantage of this technique is that the surgical approach and field are more familiar to surgeons carrying out routine vitreo-retinal surgery, while revision of the device placement and explantation can be less complex. Furthermore, locating a device in the vitreous cavity can facilitate safe heat dispersion. Functionally, it may be disadvantageous to have stimulation applied to the retinal ganglion cells (RGCs) directly, as this bypasses the residual intraretinal processing system, limiting the ability to recreate the physiological retinal topographic organization. On the other hand, it has been reported that the upstream remodeling of bipolar or amacrine cells, following PR degeneration, may necessitate a device that circumvents this.17 Also, due to the proximity of epiretinal devices to the passing axonal nerve fibers, ectopic visual percepts from inadvertent axonal stimulation could occur, thus reducing spatial resolution and obfuscating the intended stimulation pattern.
Argus II Retinal Prosthesis System
The Argus II epiretinal prosthesis (Second Sight Medical Products Inc., Sylmar, CA, USA) was the first device to receive CE marking, in 2011, and subsequently FDA approval, in 2013. It is the most widely used retinal prosthesis worldwide, with over 250 patients estimated to have undergone implantation to date.
The Argus II system is made up of an external and an implantable component (Figure 1). The external component consists of a glasses-mounted camera linked to a portable visual processing unit, which processes the image for transmission to an external communication coil (also glasses mounted). This coil provides power induction and data transmission via wireless radiofrequency (RF) telemetry to an internal matching coil, which is fixed to the sclera with a silicone scleral buckle. Once received, the RF signal is decoded back to an electrical signal and an application-specific internal circuit (ASIC) sets the output command, which passes directly to the intra-ocular retinal stimulator, comprising a 60-microelectrode array, each 200 µm in diameter, covering a 20° field of vision. The internal circuit is hermetically sealed and shown to have over 10 years’ lifespan on accelerated aging tests.18
Figure 1.
The Argus II Retinal Prosthesis System.
Source: Adapted from Second Sight Medical Products, Inc., Sylmar, CA, USA.
The Argus II phase II multicenter trial involved the implantation of 30 subjects to evaluate safety and effects on functional visual and real-world task performance. Overall, subjects performed better on grating visual acuity, square localization, and direction of movement tasks with the device on than off.19–22 The proportion of subjects reaching significant differences in these tests was maintained over 5 years’ follow-up,7 with a best recorded acuity of 1.8 logMAR (20/1262 Snellen equivalent).23 Similarly, orientation and mobility tasks were consistently better performed with the device on than off during the 5-year review period.7,22 The 10 years’ study follow-up will be completed in 2019. Other measures such as letter reading, grasping task performance, real-world functional tasks, and generation of reproducible phosphenes have all shown a significant difference with the device turned on in patients with Argus II retinal implants.24–28 In 2012, Stanga and colleagues29 demonstrated that different combinations of colors could be perceived simultaneously during paired electrode stimulation in three out of four Argus II recipients.
At 5 years postimplantation, there were 24 reported serious adverse events (SAEs) in 12 patients (40%), all of which were treatable with standard approaches.7 These were, for the most part, restricted to the early to mid postoperative period, including conjunctival erosion, dehiscence, and hypotony. There were three cases of presumed endophthalmitis, although these all occurred prior to the introduction of intravitreal antibiotics into the surgical protocol, since when there have been no further reported cases.7,19,22 Since the 3-year time point, there has only been one further reported SAE – a rhegmatogenous retinal detachment, which was successfully treated. Three devices were removed at the request of the patients, following conjunctival erosions, while two devices failed due to gradual loss of the RF link at 4 years.7,22 The precise cause of late device failure due to interrupted RF connection is not clear, but may represent exposure of the implanted electronics or receiver coil, possibly damaged during implantation. The devices have remained implanted to monitor the long-term safety in the context of this potential complication.7
The Argus II underwent NICE assessment and it was felt that more data were required to ascertain patient benefit in terms of quality of life and activities of daily living. Further implantation of 10 patients is planned later this year with a program of focused rehabilitation. A Functional Low-Vision Observer Rating Assessment (FLORA) has been refined to assess patient-reported functional vision and well-being following partial visual restoration with Argus II.30,31
Intelligent Medical Implants learning device/Intelligent Retinal Implant System II
An acute implantation study demonstrated that phosphenes could be elicited in 19 of 20 subjects, leading to the development of the Intelligent Medical Implants (IMI) Learning Device.32,33 This device consisted of a microfabricated polyimide array, with 49 platinum microelectrodes, each with a diameter of 250 µm, spaced 120 µm apart, which was chronically implanted in seven patients. Results showed a good safety profile and reasonable longevity, with patient-reported phosphenes and patterns during stimulation.34,35 The implant connected directly to an electronics module fixed to the external eye, which could only be stimulated in the clinical setting.
Since acquiring IMI in 2007, Pixium Vision S.A. has further refined the device, now known as the Intelligent Retinal Implant System (IRIS) II. The IRIS II prosthesis comprises a glasses-mounted visual interface transmitting to a pocket processor, which creates stimulation commands, which are transmitted to an extra- and intra-ocular implanted component, containing a 150-microelectrode array (Figure 2). Although this system is similar to the Argus II, the IRIS system differs in a number of ways. First, it uses a neuromorphic image sensor to respond in a continuous mode to the visual input, providing both the coordinates of changing pixels and their light intensities. The visual information encoded in this output can be divided into transient and sustained components, which can be processed using algorithms to enhance image quality and to reduce the visual scene to the most important elements. This process is designed to mimic the temporal resolution of the retina while reducing the volume of redundant visual information presented during stimulation calculation. Second, the commands generated by the pocket processor travel to the visual interface and are transferred optically via an infrared (IR) array directly to the implant, permitting higher data transfer rates and miniaturization of the implant itself. A high data transfer rate is essential for stimulating greater numbers of electrodes at a higher refresh rate while accommodating for the data communication overhead.36 Power is supplied through a separate transmitter coil system, at a lower frequency, using RF telemetry in a similar fashion to the Argus II. Finally, and perhaps most uniquely, the device includes a learning retinal encoder, which allows for individualized calibration, following as few as 100 iterations, to assign areas as excitatory or inhibitory, thus mimicking the retinal ON/OFF pathways.37,38
Figure 2.

The Intelligent Retinal Implant System (IRIS) II.
Source: Adapted from Pixium Vision S.A., Paris, France.
The IRIS II obtained CE approval in 2016 and early results were promising; 6-month data for the initial 10 subjects implanted as part of a clinical trial were presented at the International Eye and Chip Conference in 2017, reporting improvements demonstrated in square localization, direction of motion, picture recognition, and visual field testing, with a rate of 0.4 SAEs per subject. However, having conceded that the lifespan of the device was found to be shorter than expected, Pixium have postponed the trial pending further refinement of the device and surgical method.39
EPI-RET3 Retinal Implant System
The EPI-RET3 differs from the Argus and IRIS implants in that the internal components are entirely intraocular. It comprises a receiver coil and chip, that is positioned in the aphakic capsular bag and a retinal stimulator connected directly to the epiretinal stimulation array. This technology negates the need for a physical transscleral cable, instead providing the implant with energy or data via inductive links, thus reducing the risk of complications, such as infection or erosion. As with other epiretinal devices, the EPI-RET3 comprises an external camera and visual processor, which wirelessly transmits the calculated spatiotemporal pattern of stimulation pulses to the internal component (Figure 3).40
Figure 3.

The EPI-RET3 Retinal Prosthesis System.
Source: EPI-RET3 Team, RWTH Aachen, Germany.
The device uses ultrahigh-frequency-pulsed charge-controlled stimulation to reduce large stimulation artifacts. This allows for bidirectional stimulation and recording by the microelectrodes. During experiments using animal models of RP, it was noted that there was spontaneous RGC activity in areas adjacent to regions of stimulation. Furthermore, biphasic pulses appeared to have an inhibitory effect on some RGC responses, probably due to the action of residual interneurons, such as amacrine or bipolar cells. Using this bidirectional enhancement system, it is possible to characterize response types from specific retinal areas and to modify stimulation algorithms to accommodate intrinsic activity of retinal neurons and thereby deliver more effective stimulation patterns.38,41
In the first clinical trial, a basic 25-electrode system was implanted for a short period into six subjects. In all patients, the implantation was uncomplicated, except for one case of sterile hypopyon, which resolved with treatment. The system was removed at 4 weeks as planned. One case developed a giant retinal tear during removal, requiring further surgery.42,43 All six patients reported patterned phosphenes with low threshold stimulations in regions corresponding to the stimulated retina. The phosphene characterization varied greatly between patients.44
Future feasibility trials for EPI-RET3 have been focused on the development of a very large electrode arrays for epiretinal stimulation (VLARS), covering 37° of the field of vision.45 However, no results have since been published from this group.
Subretinal prostheses
The rationale behind the placement of a subretinal implant is that by positioning the device at the level of the degenerated PRs, the intrinsic signal processing capacity of the retinal interneurons can be exploited, producing a more physiological form of vision, with less demand for image processing. Moreover, the device is situated closer to the target retina and may benefit from the natural retinal signal amplification, requiring lower stimulation intensities. This, however, assumes retention of the anatomical organization of the retinal interneuron network, which is unlikely to be the case, even prior to detectable PR cell death.46,47
Unless the system has intrinsic photosensitivity and amplification capacity, it will, like the epiretinal devices, require a power source and a connection serving the delivery of data. In terms of surgery, some reports have suggested that placement of subretinal implants can be technically more challenging, both due to retina-retinal pigment epithelium (RPE) adhesion, as a consequence of the underlying degeneration, and the surgical approach being less familiar to surgeons carrying out routine retinal surgery.
Boston Retinal Implant
The Boston Retinal Implant Project (BRIP) was one of the first endeavors of its kind and led one of the earliest acute trials in human subjects, wherein it was shown that reproducible percepts could be induced with single-electrode stimulation in patients with end-stage RP and one patient with normal vision prior to exenteration for orbital cancer.48 The BRIP device is, in many respects, similar in design to the Argus II implant, but it is implanted in the subretinal space, in order to obviate the need for device fixation and to minimize gliosis that may occur with tack insertion.49
The BRIP group is currently performing preclinical trials for a 256-channel device, with a view to performing phase I clinical trials in the near future. The group is committed to developing an implant that provides functionally ‘useful’ vision, before adopting a corporate strategy for ongoing development.50
Artificial silicon retina
This device, developed by Optobionics (Glen Ellyn, IL, USA), was the first passive prosthesis to attempt wireless retinal stimulation using ambient light. The 2-mm-wide, 25-µm-thick artificial silicon retina (ASR) array consists of 5000 micro-photodiodes of 20-µm-diameter associated with 9-µm-diameter iridium-tipped microelectrodes and separated by 5 µm. In a pilot study of six patients, in whom the implant was placed in the superior retina, it was demonstrated that phosphenes could be perceived in the region of the field of vision corresponding to the device in four patients. Furthermore, overall visual function was enhanced in retinal areas distant from the implant, with reported improvements in visual function. This led the group to suggest that either the surgery or the focal electrical stimulation by the implant could induce a generalized neurotrophic effect on the retina,51 which was also demonstrated on rodent models.52,53 A further 4 patients were implanted, giving a total of 10 patients implanted with the ASR chip, 6 of whom received long-term follow-up. The ASR implants demonstrated good safety and longevity profiles,54 and while a temporary improvement in generalized visual function was demonstrated, compared with the control eye, this was ascribed to the effect of neuroprotective growth factors rather than the retinal prosthesis per se. It has been concluded that a device relying on ambient light alone is unable to generate sufficient photocurrent to directly stimulate a meaningful number of neurons. The company has subsequently closed and there have been no further published results from this group.55 Ultimately, however, the pioneering work by this group has since led to the development of promising next-generation photovoltaic systems.
Alpha IMS and AMS
The Alpha IMS (Retina Implant AG, Reutlingen, Germany) is the first and only subretinal implant to obtain CE marking, which was granted in 2013. In a similar fashion to the ASR, it incorporates a photovoltaic array, termed a multiphotodiode array (MPDA), which comprises a 3-mm2 microchip containing 1500 independent photodiode–amplifier–electrode units, each of which will convert ambient luminance into an electrical signal. However, it differs from the ASR in that it is an ‘active’ device, using an extrinsic power source to amplify the signal. This is supplied via a silicone supply cable, which links to a fixation pad looped through the orbit, passing subcutaneously and then under the temporal muscle to a subdermal coil, which is fixed to the postauricular cranial bone. A removable external coil magnetically attaches to the subdermal coil, allowing electromagnetic power induction and control of contrast sensitivity and brightness from a handheld unit.56,57 Due to the extra-orbital placement of the induction coil and the intra-ocular placement of the array, coordination between different surgical specialist teams is required, leading to longer operating times. Moreover, RPE degeneration and adhesion to the retina can lead to difficulty with subfoveal device placement. These factors may contribute to the higher reported rates of device repositioning, replacement surgery, and device failure.57,58
The Alpha IMS clinical trial in 2010–2014 aimed to assess the improvement in daily living and mobility, as well as visual acuity and object recognition. Patient experience of the device in daily life varied from six subjects (21%) who reported very good experiences, recognizing letters or unknown objects, including houses and cars, to eight subjects (28%) who reported no benefit at all. It was reported that 25 subjects (86%) could perceive light with the implant, with significant improvement in light localization, while 6 subjects could detect motion. The best visual acuity recorded on contrast-reversal Landolt C-ring testing was 20/546. Object recognition tests revealed significant improvement with the device on during the initial 3 months but fell below significance from month 6.59,60 The safety profile of the device was generally felt to be clinically acceptable, with only two SAEs (among 75 reported total AEs) in nine subjects within 1 year of implantation.61
The subsequent iteration, the Alpha AMS, which is larger and incorporates 1600 photodiode complexes, received CE approval in 2016 (Figure 4). Results of 1 year showed similar functional benefits and number of SAEs (eight in nine subjects) to the Alpha IMS, although the authors report a considerable improvement in the functional longevity of the device.6
Figure 4.
The Retina Implant Alpha AMS System.
Source: Adapted from Retina Implant AG, Reutlingen, Germany.
Photovoltaic Retinal Implant (PRIMA) bionic vision system
This relatively recent venture (Pixium Vision S.A.) has taken various pre-existing implant concepts and created a novel model of photovoltaic stimulation. In this modular array setup, a 1-mm-wide hexagonal chip, containing 142-pixel cells of 30-µm-thick, is inserted subretinally (Figure 5). Each pixel receives visual information in the form of pulsed near-IR light directly from a pair of specially constructed glasses. This photic energy passes from a stimulating electrode to a return electrode, each connected to multiple photodiodes in series and coated in sputtered iridium oxide. In turn, these photodiodes generate an electrical current that polarizes the adjacent neuronal tissue. This modular arrangement is thought to both improve spatial resolution and also be more readily scalable to a larger visual field, without the need for transscleral wires or additional power induction, as in the Alpha IMS.62–64
Figure 5.

Schematic of the Photovoltaic Retinal Implant (PRIMA) Bionic Vision System. Inset: device in a patient with geographic atrophy.
Source: Adapted from Palanker et al, Stanford University, and Pixium Vision S.A., Paris, France.
Preclinical results using this approach in animal models have been encouraging. Visual-evoked potential (VEP) testing in implanted Royal College of Surgeons rats in response to photovoltaic stimulation demonstrated a similar shape and amplitude to VEPs in wild-type rats, with decreased latency due to the absence of phototransduction. The amplitude of the VEP could also be scaled by modulating light intensity with liquid crystal displays or pulse duration with digital light processing micro-mirror arrays.65 Contrast sensitivity, on the other hand, was limited, with only 100% contrast eliciting a VEP response above the noise level.66 By switching from cathodic-first pulses of current to anodic-first, it has been shown in vitro and in vivo that stimulation thresholds can be decreased well below the ocular safety limit for near-infrared (NIR) irradiance while retaining spatial frequency.66–68 It has been postulated that an equivalent spatial resolution in humans could yield a grating acuity of 20/250, with scope to further reduce pixel size and pitch.69
Five patients with dry AMD have been implanted with the PRIMA device in France, with plans to implant five more in the United States during 2018, as part of a safety and performance evaluation feasibility study over 36 months. Preliminary results are anticipated in 2019.70
Suprachoroidal prostheses
The third position of placement of prostheses for local retinal stimulation has been the suprachoroidal space. In this position, the system does not necessitate transvitreal surgery and is therefore potentially less invasive and more easily accessible for repair or replacement. However, the suprachoroidal space is highly vascular and there is a significant risk of hemorrhage and there remains a risk of fibrosis postimplantation. Furthermore, due to its distance from the neurosensory retina, this design appears to require greater stimulation power to elicit visual percepts. Suprachoroidal placement also risks greater spread of current, thereby reducing the spatial resolution.
Bionic Vision Australia
The Bionic Vision Australia (BVA) team has developed a series of suprachoroidal implant prototypes over the past 10 years. The first of these was a 24-channel system, consisting of 20 stimulation channels and 4 return electrodes. In a similar fashion to the Alpha AMS and cochlear implants, this system involves dissection of the temporalis muscle for attachment of a percutaneous connector to the bone. From there the connecting wire is passed through a tunnel in the muscle fascia and via a lateral orbitotomy and peritomy, at which point the lateral muscle is temporarily disinserted to allow for placement of the array into the suprachoroidal space.71,72 This device has no photovoltaic properties, relying on a head-mounted camera and image processor to provide the electrode stimulation patterns.
In 2012, three subjects with advanced RP were implanted for 2 years as part of a pilot study. The surgery took between 3 and 4 h and it was reported that all patients developed a combined subretinal and suprachoroidal hemorrhage postoperatively.72 During testing, phosphene location, shape, and size were mapped using a finger-mounted motion tracker and eye-facing camera to monitor gaze. Phosphenes could be elicited in all patients, and although variable in character, location, and stimulation thresholds, they were reported to be controllable and retinotopically locatable in two patients.73,74 Light localization, optotype recognition, and grating acuity tests, as well as tasks of daily living, were performed using a head-mounted camera. Light localization was better than chance in all participants, while only one subject completed the visual acuity task, averaging 20/8397, significantly better with device on than with the device off.72,75 In a series of psychophysical tasks delivered by direct electrode stimulation, two of the subjects demonstrated better than chance character recognition and static object localization, while one was able to detect dynamic image trajectory.76 At the time of explantation, electrical stimulation was still possible, although it was noted in all cases that a fibrous capsule had developed around the implant.77
The primary limitations of suprachoroidal stimulation relate to the proximity of the device to the retinal neurons. The BVA group is developing a next-generation 44-channel fully implantable device,78 while also designing a 99-channel device, the Phoenix-99, which will incorporate a dual monopolar and hexapolar (‘quasi-monopolar’) stimulation pattern, to try and address the issues of retinotopic discrimination and high stimulation thresholds.73,79
Suprachoroidal–transretinal stimulation
The suprachoroidal–transretinal stimulation (STS) system is under development by Japan’s Artificial Vision Project in conjunction with NIDEK. Like the BVA system, the STS requires a temporalis incision and tunneled connection between a decoder, an internal coil and a stimulating electrode array, and return electrode. Once suprathreshold light is detected by a glasses-mounted camera and processed by a computer within the arm of the spectacles, the external coil will relay a signal via the secondary coil to the decoder, which, in turn, generates a biphasic pulse to stimulate individual electrodes. Unlike other systems, the current STS consists of a ‘3D’ (three-dimensional) 49-microelectrode array, with electrodes that protrude from the array by 0.3 mm, which is inserted into a 6 mm × 5 mm scleral pocket. Power is provided externally through a portable battery pack.80
In a pilot study of two patients using a prototype nine-electrode implant, it was shown that phosphenes could be reproducibly elicited in the area of the visual field corresponding to the implant, during direct stimulation. Using a headband-mounted camera, following which the images are converted to 3 × 3 squares with a pixel resolution of 40 × 40, both patients could identify and discriminate objects using head scanning with between four and six electrodes, while one patient could also detect motion and perform grasping tasks better than by chance.81 Following the surgical success of both single and dual 49-electode arrays in animal models, three patients underwent implantation of this second-generation device. While the safety profile of the device was reassuring, with no SAEs requiring further surgery at 1 year, the tests of function were less consistent. One subject could localize a square better with the device on during all of the follow-up, while two subjects were able to walk along a white line and recognize an everyday object better than chance, but not reproducibly at separate time points.82 One subject with Stargardt disease and hand movements vision in the left eye underwent implantation with an STS device in the fellow eye. Results suggest that the subject could reach more accurately using a combination of natural and artificial vision than with residual natural vision alone.83 Larger numbers are required to draw firmer conclusions about the efficacy of suprachoroidal and transscleral implants in their present formats; however, results to date suggest greater limitations to this approach than for epiretinal or subretinal implants.
Challenges in prosthetic vision
The classification of retinal prostheses according to their anatomical placement serves best to demonstrate the different surgical approaches and theoretical differences in which residual retinal cells are stimulated. However, apart from these aspects, all devices face challenges in the form of image capture, processing, delivery of data and power, biocompatibility, and hermeticity. During the last quarter century, the field has witnessed progress from intra-operative focal electrode stimulation to chronic implantation of multi-electrode arrays for over 10 years, demonstrating significant, albeit coarse, functional improvement. In general, advances in image processing algorithms and optical data transfer rates, combined with developments in the field of microelectronics and material microfabrication, continue to drive the field forward, projecting a hugely encouraging outlook for the future progress of visual restorative therapy.
To date, no single approach has yielded results that suggest a significant advantage over other systems, but the substantial progress over the past three decades represents unprecedented endeavor, innovation, and collaboration, across the field as a whole.
Assessing functional outcomes
One of most pressing issues that has begun to limit the broader use of prosthetic retinal devices is how to assess its ‘usefulness’ and function in terms of patient benefit and consequently how to predict in which direction to develop these devices. Numerous studies have incorporated performance-based measures and self-reporting questionnaires to attempt to understand the relative importance of visual parameters in performance of everyday tasks in visually impaired subjects. This has demonstrated the importance of visual acuity, visual field, and contrast sensitivity for acceptable day-to-day visual functioning.84–88 Simulation studies can estimate the visual requirements to deliver a sufficient image resolution and field of view with a prosthetic system, in order to perform useful tasks. Overall, a minimum spatial resolution of 3–4 pixels per degree2 (i.e. a 600–1000 pixel array with a 15° × 15° field of view) is thought to be able to permit an acceptable accuracy in pointing, manipulation, mobility, and object recognition activities,89–92 and even higher resolution is necessary for reading.93,94 This is approximately 10 times greater than the resolution provided by the current Argus II system.
Most conventional tests of basic visual function such as ETDRS and Snellen visual acuity are not validated for quantification of vision below a certain threshold, though calculated equivalents in these scales are often mentioned in published articles and in this review. Coarser tests of function, such as grating visual acuity, Basic Light and Motion Assessment (BaLM) and the Freiburg Visual Acuity Test (FrACT), have shown some capacity to deliver reliable evaluations of ULV in some studies.95–97
In terms of functional outcomes, self-reporting and performance-based testing can give some indication of qualitative benefit. However, there is currently no universally accepted functional outcome measure for providing reliable and quantitative evidence for the functional value of therapies in those with ultra-low vision (ULV). Functional vision tests in ULV should not only be valid, reliable, and repeatable in the conventional sense, but ought to also have ecological validity, that is, relate to an appreciable change in the subject’s real-world task performance. Furthermore, they should be sensitive to response to treatment and allow estimation of a quantifiable ‘minimally important difference’, at which a subject perceives a useful functional improvement.98
Many of the aforementioned functional tests, such as square localization, recognition of white objects on a black background, or following a white line on the floor, are limited in terms of ecological validity due to their departure from a real-world environment. On the other hand, real-world functional assessments, such as FLORA, which involve an observer-rated calculation of visual ability during activities of daily living in residential settings, suffer from the inability to provide a standardized metric for measuring functional benefit across different subjects. One solution, in the context of navigational function, can be offered using standardized, simulated real-world environments, such as the Pedestrian Accessibility and Movement Environment Laboratory at UCL, although this is expensive to manufacture, maintain, and reproduce across the number of groups working in the area. Other approaches include the use of salience maps to determine the spatial allocation of a subject’s visual attention toward objects of interest within a presented visual scene. Simulated tests of picture and face discrimination have demonstrated good ability of subjects to identify salient features, with a pronounced learning effect during retesting.99,100
Currently, progress in the field of restorative visual medicine is reliant on the validation of a standardized test battery that incorporates both objective and subjective measures of visual task performance, in order to demonstrate a reliable metric of functional benefit. As increasing numbers of patients with ULV receive various emerging therapies, we anticipate that this demand will be met.
Hardware and software constraints
Using basic tests of visual function, the highest estimated acuity achieved to date is with the Alpha IMS, with which 20/546 was recorded, followed by 20/1262 with the Argus II.6,23 This is significantly inferior to natural vision, both in terms of resolution and form. Spatial resolution of prosthetic systems is limited by several factors, including electrode density, size, number and pitch, electrode contact, and visual encoding. Issues with temporal resolution and image persistence further limit the interpretation of prosthetic vision.101
Existing electrode arrays are thought to have a theoretical maximum resolution that is at least 12 times less than that of the normal retina.102 The maximal electrode density is currently limited by heat generation that occurs during signal transmission. However, even if it is possible to develop an implant with a similar size and density of microelectrodes to native cone PRs, there would still exist the biological challenge of recreating the visual encoding capacity of the retinal interneurons, especially at the fovea, where the neuronal layers do not directly overlie the PRs. In theory, a maximum pixel diameter of about 50 µm, separated by 25 µm, would be necessary to achieve a spatial frequency equivalent to the minimum angle of resolution achieved in 20/200 vision (the approximate level of visual impairment). At present, the MPDA systems containing autonomous pixels appear to hold the most promise for maximizing electrode density at this scale but have not yet achieved results that reflect the theoretical limit of the devices, probably, in part, due to the aforementioned remodeling process that the degenerative retina undergoes17 and electrode–target tissue distance. Incorporation of bidirectional stimulation, as in the EPI-RET3, is important to allow signal feedback and modulation of the stimulation algorithms to exploit any residual retinal processing and mimic RGC receptive fields, thus enhancing contrast and spatial resolution.38
The issue of electrode contact is being addressed by some groups using 3D electrodes to improve local contact, such as the NIDEK group and the Nano Retina group, who are developing the Bio-Retina array with nano-coated electrode tips.103 While embedded electrodes may reduce charge density and stimulation artifact, it is conceivable that such penetration of the retina could lead to greater risk of complication, such as hemorrhage or further retinal degeneration, and make removal or repositioning of devices more problematic.
In addition, there are hardware constraints limiting the field of vision that current implants can deliver. In the case of external image capture systems, the patient must become adept at head scanning, both to maximize the accumulation of information from a visual scene and to prevent ‘fading’ of images due to repetitive stimulation. This latter issue can be partly resolved through the use of photovoltaic systems or an intra-ocular camera, which exploits the natural microsaccadic eye movements to prevent this fading phenomenon and also avoids any decoupling of the visual interface and stimulating array when the head or eye moves. Development of very large electrode arrays (VLARS) is underway45 but will ultimately be a trade-off between expanding the field of vision, minimizing implantation trauma, and coping with high levels of heat dissipation. The concept of using modular elements, as in the PRIMA device, to enlarge the functional visual field, may represent a preferable strategy.
The longevity of the subretinal photovoltaic systems appears to be shorter than for epiretinal devices, probably because of the current limitations in material engineering. Development is underway for novel biocompatible materials, such as laser-microstructured diamond electrode arrays, with greater longevity and chemical stability,104 or liquid crystal polymers that are also ultra-thin, lightweight, and deformable.105 In addition, the field of tissue electronics, concerned with the development of organic conductive and semi-conductive polymers, is emerging as an alternative to inorganic systems. Initial animal models have demonstrated efficacy, and it is postulated that the graded modulation of neurotransmitter release afforded via an organic array may create a more physiological interaction with the neuronal tissue, potentially enhancing the resultant spatial resolution.106–108
There is also much focus on how software algorithms can be refined to filter the image and detect relevant features of the visual scene. This image processing method, termed saliency mapping, has been used to develop computational models for rapid recognition and segmentation of image information for over a decade and is now widely utilized in the emerging field of computer vision and machine learning.109–112 In the field of retinal prosthetics, this information can be used to apply transformations to the encoded stimulation pattern, such as edge detection, grayscale histogram equalization, contrast and intensity enhancement, as well as image magnification.112,113 Simulation studies suggest that use of such processing algorithms can boost task performance, including face and object recognition and navigation.114–118
Finally, another factor that is certain to play a role in the future success of retinal prosthetics is the ability of recipients to adapt to using this novel but rudimentary visual input. The relatively poorly understood phenomenon of cortical plasticity and perceptual learning has been thoroughly addressed with respect to visual restoration in excellent previous reviews.119,120
Conclusion
The field of visual restorative therapy is rapidly advancing and holds great promise for the introduction of real, measurable treatments of blinding conditions in the near future. Although not limited to retinal prostheses, with significant progress being made in other strategies, such as optogenetics, stem cells, and gene therapy, this represents the most advanced form of treatment for profound vision loss that is currently available. It is likely that the future will see integration of prosthetic devices with regenerative medicine technologies, in the form of ‘biohybrid’ implants.
This review summarizes just some of the considerable progress has been made in the field of retinal prostheses in the past decades. However, the remaining challenges are as diverse as they are numerous, and overcoming them will rely on continued close collaboration between engineers, healthcare workers, industry, and patients to eventually transform this concept from science fiction into science fact.
Footnotes
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
Conflict of interest statement: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Contributor Information
Edward Bloch, Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK; NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK.
Yvonne Luo, NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK; East Kent Hospitals University NHS Foundation Trust, Kent, UK.
Lyndon da Cruz, Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK; NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK.
References
- 1. Hartong DT, Berson EL, Dryja TP. Retinitis pigmentosa. Lancet 2006; 368: 1795–1809. [DOI] [PubMed] [Google Scholar]
- 2. Medeiros NE, Curcio CA. Preservation of ganglion cell layer neurons in age-related macular degeneration. Invest Ophthalmol Vis Sci 2001; 42: 795–803. [PubMed] [Google Scholar]
- 3. Liew G, Michaelides M, Bunce C. A comparison of the causes of blindness certifications in England and Wales in working age adults (16–64 years), 1999–2000 with 2009–2010. BMJ Open 2014; 4: e004015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Owen CG, Jarrar Z, Wormald R, et al. The estimated prevalence and incidence of late stage age related macular degeneration in the UK. Br J Ophthalmol 2012; 96: 752–756. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. da Cruz L, Fynes K, Georgiadis O, et al. Phase 1 clinical study of an embryonic stem cell-derived retinal pigment epithelium patch in age-related macular degeneration. Nat Biotechnol 2018; 36: 328–337. [DOI] [PubMed] [Google Scholar]
- 6. Stingl K, Schippert R, Bartz-Schmidt KU, et al. Interim results of a multicenter trial with the new electronic subretinal implant alpha AMS in 15 patients blind from inherited retinal degenerations. Front Neurosci 2017; 11: 445. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. da Cruz L, Dorn JD, Humayun MS, et al. Five-year safety and performance results from the Argus II Retinal Prosthesis System clinical trial. Ophthalmology 2016; 123: 2248–2254. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Schwartz SD, Tan G, Hosseini H, et al. Subretinal transplantation of embryonic stem cell-derived retinal pigment epithelium for the treatment of macular degeneration: an assessment at 4 years. Invest Ophthalmol Vis Sci 2016; 57: ORSFc1–9. [DOI] [PubMed] [Google Scholar]
- 9. MacLaren RE, Groppe M, Barnard AR, et al. Retinal gene therapy in patients with choroideremia: initial findings from a phase 1/2 clinical trial. Lancet 2014; 383: 1129–1137. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Jacobson SG, Cideciyan AV, Ratnakaram R, et al. Gene therapy for leber congenital amaurosis caused by RPE65 mutations: safety and efficacy in 15 children and adults followed up to 3 years. Arch Ophthalmol 2012; 130: 9–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Foerster O. Beiträge zur Pathophysiologie der Sehbahn und der Sehsphäre. J Psychol Neurol 1929; 39: 463–485. [Google Scholar]
- 12. Brindley GS, Lewin WS. The sensations produced by electrical stimulation of the visual cortex. J Physiol (Lond) 1968; 196: 479–493. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Holmes G. Disturbances of vision by cerebral lesions. Br J Ophthalmol 1918; 2: 353–384. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Potts AM, Inoue J. The electrically evoked response (EER) of the visual system II: effect of adaptation and retinitis pigmentosa. Invest Ophthalmol Vis Sci 1969; 8: 605–612. [PubMed] [Google Scholar]
- 15. Zrenner E, Greger B. Chapter 1 – restoring vision to the blind: the new age of implanted visual prostheses. Transl Vis Sci Technol 2014; 3: 3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Elmannai W, Elleithy K. Sensor-based assistive devices for visually-impaired people: current status, challenges, and future directions. Sensors 2017; 17: 565. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Marc R, Pfeiffer R, Jones B. Retinal prosthetics, optogenetics, and chemical photoswitches. ACS Chem Neurosci 2014; 5: 895–901. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Luo YH-L, da Cruz L. The Argus(®) II retinal prosthesis system. Prog Retin Eye Res 2016; 50: 89–107. [DOI] [PubMed] [Google Scholar]
- 19. Humayun MS, Dorn JD, Ahuja AK, et al. Preliminary 6 month results from the Argus II epiretinal prosthesis feasibility study. Conf Proc IEEE Eng Med Biol Soc 2009; 2009: 4566–4568. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Dorn JD, Ahuja AK, Caspi A, et al. The detection of motion by blind subjects with the epiretinal 60-electrode (Argus II) retinal prosthesis. JAMA Ophthalmol 2013; 131: 183–189. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Ahuja AK, Dorn JD, Caspi A, et al. Blind subjects implanted with the Argus II retinal prosthesis are able to improve performance in a spatial-motor task. Br J Ophthalmol 2011; 95: 539–543. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Ho AC, Humayun MS, Dorn JD, et al. Long-term results from an epiretinal prosthesis to restore sight to the blind. Ophthalmology 2015; 122: 1547–1554. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Humayun MS, Dorn JD, da Cruz L, et al. Interim results from the international trial of Second Sight’s visual prosthesis. Ophthalmology 2012; 119: 779–788. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. da Cruz L, Coley BF, Dorn J, et al. The Argus II epiretinal prosthesis system allows letter and word reading and long-term function in patients with profound vision loss. Br J Ophthalmol 2013; 97: 632–636. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Luo YH-L, Zhong JJ, da Cruz L. The use of Argus® II retinal prosthesis by blind subjects to achieve localisation and prehension of objects in 3-dimensional space. Graefes Arch Clin Exp Ophthalmol 2015; 253: 1907–1914. [DOI] [PubMed] [Google Scholar]
- 26. Dagnelie G, Christopher P, Arditi A, et al. Performance of real-world functional vision tasks by blind subjects improves after implantation with the Argus® II retinal prosthesis system. Clin Experiment Ophthalmol 2017; 45: 152–159. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Luo YH-L, Zhong JJ, Clemo M, et al. Long-term repeatability and reproducibility of phosphene characteristics in chronically implanted Argus II retinal prosthesis subjects. Am J Ophthalmol 2016; 170: 100–109. [DOI] [PubMed] [Google Scholar]
- 28. Kotecha A, Zhong J, Stewart D, et al. The Argus II prosthesis facilitates reaching and grasping tasks: a case series. BMC Ophthalmol 2014; 14: 71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Stanga PE, Sahel J-A, da Cruz L, et al. Patients blinded by outer retinal dystrophies area able to perceive simultaneous colors using the Argus® II retinal prosthesis system. Invest Ophthalmol Vis Sci 2012; 53: 6952. [Google Scholar]
- 30. Geruschat DR, Flax M, Tanna N, et al. FLORA™: phase I development of a functional vision assessment for prosthetic vision users. Clin Exp Optom 2015; 98: 342–347. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Geruschat DR, Richards TP, Arditi A, et al. An analysis of observer-rated functional vision in patients implanted with the Argus II Retinal Prosthesis System at three years. Clin Exp Optom 2016; 99: 227–232. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Richard G, Feucht M, Bornfeld N, et al. Multicenter study on acute electrical stimulation of the human retina with an epiretinal implant: clinical results in 20 patients. Invest Ophthalmol Vis Sci 2005; 46: 1143. [Google Scholar]
- 33. Keserü M, Feucht M, Bornfeld N, et al. Acute electrical stimulation of the human retina with an epiretinal electrode array. Acta Ophthalmol 2012; 90: e1–e8. [DOI] [PubMed] [Google Scholar]
- 34. Keserü M, Post N, Hornig R, et al. Long term tolerability of the first wireless implant for electrical epiretinal stimulation. Invest Ophthalmol Vis Sci 2009; 50: 4226. [Google Scholar]
- 35. Richard G, Keserü M, Feucht M, et al. Visual perception after long-term implantation of a retinal implant. Invest Ophthalmol Vis Sci 2005; 49: 1786. [Google Scholar]
- 36. Zhou M, Yuce MR, Liu W. A non-coherent DPSK data receiver with interference cancellation for dual-band transcutaneous telemetries. Conf Proc IEEE Eng Med Biol Soc 2008; 43: 2003–2012. [Google Scholar]
- 37. Hornig R, Dapper M, Le Joliff E, et al. Pixium vision: first clinical results and innovative developments. In: Gabel VP. (ed.) Artificial vision. Cham: Springer, 2016, pp. 99–113. [Google Scholar]
- 38. Eckmiller R, Neumann D, Baruth O. Tunable retina encoders for retina implants: why and how. J Neural Eng 2005; 2: S91–S104. [DOI] [PubMed] [Google Scholar]
- 39. Muqit M, LeMer Y, De Rothschild A, et al. Results at 6 months, http://www.pixium-vision.com/en/clinical-trial/retinitis-pigmentosa-iris-ii/results-at-6-months (2017, accessed 27 August 2018).
- 40. Walter P. A fully intraocular approach for a bi-directional retinal prosthesis. In: Gabel VP. (ed.) Artificial vision. Cham: Springer, 2016, pp. 151–161. [Google Scholar]
- 41. Schloesser M, Cota O, Heil R, et al. Embedded device for simultaneous recording and stimulation for retina implant research. In: SENSORS, Baltimore, MD, 3–6 November 2013, pp. 1–4. New York: IEEE. [Google Scholar]
- 42. Roessler G, Laube T, Brockmann C, et al. Implantation and explantation of a wireless epiretinal retina implant device: observations during the EPIRET3 prospective clinical trial. Invest Ophthalmol Vis Sci 2009; 50: 3003–3008. [DOI] [PubMed] [Google Scholar]
- 43. Menzel-Severing J, Laube T, Brockmann C, et al. Implantation and explantation of an active epiretinal visual prosthesis: 2-year follow-up data from the EPIRET3 prospective clinical trial. Eye (Lond) 2012; 26: 501–509. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44. Klauke S, Goertz M, Rein S, et al. Stimulation with a wireless intraocular epiretinal implant elicits visual percepts in blind humans. Invest Ophthalmol Vis Sci 2011; 52: 449–455. [DOI] [PubMed] [Google Scholar]
- 45. Waschkowski F, Hesse S, Rieck A, et al. Development of very large electrode arrays for epiretinal stimulation (VLARS). Biomed Eng Online 2014; 13: 11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Marc RE, Jones BW, Watt CB, et al. Neural remodeling in retinal degeneration. Prog Retin Eye Res 2003; 22: 607–655. [DOI] [PubMed] [Google Scholar]
- 47. Jones BW, Marc RE. Retinal remodeling during retinal degeneration. Exp Eye Res 2005; 81: 123–137. [DOI] [PubMed] [Google Scholar]
- 48. Rizzo JF, III, Wyatt J, Loewenstein J, et al. Methods and perceptual thresholds for short-term electrical stimulation of human retina with microelectrode arrays. Invest Ophthalmol Vis Sci 2003; 44: 5355–5361. [DOI] [PubMed] [Google Scholar]
- 49. Rizzo JF, Shire DB, Kelly SK, et al. Development of the Boston retinal prosthesis. Conf Proc IEEE Eng Med Biol Soc 2011; 2011: 3135–3138. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Rizzo JF. Update on retinal prosthetic research: the Boston Retinal Implant Project. J Neuroophthalmol 2011; 31: 160–168. [DOI] [PubMed] [Google Scholar]
- 51. Chow AY. The Artificial Silicon Retina microchip for the treatment of vision loss from retinitis pigmentosa. Arch Ophthalmol 2004; 122: 460. [DOI] [PubMed] [Google Scholar]
- 52. Pardue MT, Phillips MJ, Yin H, et al. Possible sources of neuroprotection following subretinal silicon chip implantation in RCS rats. J Neural Eng 2005; 2: S39–S47. [DOI] [PubMed] [Google Scholar]
- 53. Pardue MT, Phillips MJ, Yin H, et al. Neuroprotective effect of subretinal implants in the RCS rat. Invest Ophthalmol Vis Sci 2005; 46: 674–682. [DOI] [PubMed] [Google Scholar]
- 54. Chow AY, Bittner AK, Pardue MT. The artificial silicon retina in retinitis pigmentosa patients (an American Ophthalmological Association thesis). Trans Am Ophthalmol Soc 2010; 108: 120–154. [PMC free article] [PubMed] [Google Scholar]
- 55. Optobionics website: www.optobionics.com (accessed 27 August 2018).
- 56. Zrenner E, Bartz-Schmidt KU, Benav H, et al. Subretinal electronic chips allow blind patients to read letters and combine them to words. Proc Biol Sci 2011; 278: 1489–1497. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57. Zrenner E, Bartz-Schmidt KU, Besch D, et al. The subretinal implant ALPHA: implantation and functional results. In: Gabel VP (ed.) Artificial vision. Cham: Springer, 2016, pp. 65–86. [Google Scholar]
- 58. Gekeler F, Sachs H, Kitiratschky VBD, et al. Re-alignment and explantation of subretinal prostheses: surgical aspects and proteomic analyses. Invest Ophthalmol Vis Sci 2013; 54: 1036. [Google Scholar]
- 59. Stingl K, Bartz-Schmidt KU, Besch D, et al. Subretinal visual implant Alpha IMS – clinical trial interim report. Vision Res 2015; 111: 149–160. [DOI] [PubMed] [Google Scholar]
- 60. Stingl K, Bartz-Schmidt KU, Besch D, et al. Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS. Proc Biol Sci 2013; 280: 20130077. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61. Kitiratschky VBD, Stingl K, Wilhelm B, et al. Safety evaluation of ‘retina implant alpha IMS’ – a prospective clinical trial. Graefes Arch Clin Exp Ophthalmol 2014; 253: 381–387. [DOI] [PubMed] [Google Scholar]
- 62. Lee DY, Lorach H, Huie P, et al. Implantation of modular photovoltaic subretinal prosthesis. Ophthalmic Surg Lasers Imaging Retina 2016; 47: 171–174. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63. Wang L, Mathieson K, Kamins TI, et al. Photovoltaic retinal prosthesis: implant fabrication and performance. J Neural Eng 2012; 9: 046014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64. Lorach H, Palanker D. High resolution photovoltaic subretinal prosthesis for restoration of sight. In: Gabel VP. (ed.) Artificial vision. Cham: Springer, 2016, pp. 115–124. [Google Scholar]
- 65. Mandel Y, Goetz G, Lavinsky D, et al. Cortical responses elicited by photovoltaic subretinal prostheses exhibit similarities to visually evoked potentials. Nat Commun 2013; 4: 564. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66. Lorach H, Goetz G, Mandel Y, et al. Performance of photovoltaic arrays in-vivo and characteristics of prosthetic vision in animals with retinal degeneration. Vision Res 2015; 111: 142–148. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67. Boinagrov D, Pangratz-Fuehrer S, Goetz G, et al. Selectivity of direct and network-mediated stimulation of the retinal ganglion cells with epi-, sub- and intraretinal electrodes. J Neural Eng 2014; 11: 026008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68. Loudin JD, Cogan SF, Mathieson K, et al. Photodiode circuits for retinal prostheses. IEEE Trans Biomed Circuits Syst 2011; 5: 468–480. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69. Lorach H, Goetz G, Smith R, et al. Photovoltaic restoration of sight with high visual acuity. Nat Med 2015; 21: 476–482. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70. Clinical Trial. http://www.pixium-vision.com/en/clinical-trial/overview (accessed 27 August 2018).
- 71. Saunders AL, Williams CE, Heriot W, et al. Development of a surgical procedure for implantation of a prototype suprachoroidal retinal prosthesis. Clin Exp Ophthalmol 2014; 42: 665–674. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72. Ayton LN, Blamey PJ, Guymer RH, et al. First-in-human trial of a novel suprachoroidal retinal prosthesis. PLoS ONE 2014; 9: e115239. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73. Ayton LN, Suaning GJ, Lovell NH, et al. Suprachoroidal retinal prostheses. In: Gabel VP. (ed.) Artificial vision. Cham: Springer, 2016, pp. 125–138. [Google Scholar]
- 74. Sinclair NC, Shivdasani MN, Perera T, et al. The appearance of phosphenes elicited using a suprachoroidal retinal prosthesis. Invest Ophthalmol Vis Sci 2016; 57: 4948–4961. [DOI] [PubMed] [Google Scholar]
- 75. Petoe MA, McCarthy CD, Shivdasani MN, et al. Determining the contribution of retinotopic discrimination to localization performance with a suprachoroidal retinal prosthesis. Invest Ophthalmol Vis Sci 2017; 58: 3231–3239. [DOI] [PubMed] [Google Scholar]
- 76. Shivdasani MN, Sinclair NC, Gillespie LN, et al. Identification of characters and localization of images using direct multiple-electrode stimulation with a suprachoroidal retinal prosthesis. Invest Ophthalmol Vis Sci 2017; 58: 3962–3974. [DOI] [PubMed] [Google Scholar]
- 77. Allen PJ, Ayton LN, Yeoh J, et al. A prototype suprachoroidal retinal prosthesis: device reliability and patient safety report of a 2 year clinical study. Invest Ophthalmol Vis Sci 2015; 56: 750. [Google Scholar]
- 78. Abbott CJ, Nayagam DAX, Luu CD, et al. Safety Studies for a 44-channel suprachoroidal retinal prosthesis: a chronic passive study. Invest Ophthalmol Vis Sci 2018; 59: 1410–1424. [DOI] [PubMed] [Google Scholar]
- 79. Suaning GJ, Lovell NH, Lehmann T. Neuromodulation of the retina from the suprachoroidal space: the Phoenix 99 implant. In: 2014 IEEE biomedical circuits and systems conference (BioCAS), Lausanne, 22–24 October 2014, pp. 256–259. New York: IEEE. [Google Scholar]
- 80. Fujikado T. Retinal prosthesis by suprachoroidal-transretinal stimulation (STS), Japanese approach. In: Gabel VP. (ed.) Artificial vision. Cham: Springer, 2016, pp. 139–150. [Google Scholar]
- 81. Fujikado T, Kamei M, Sakaguchi H, et al. Testing of semichronically implanted retinal prosthesis by suprachoroidal-transretinal stimulation in patients with retinitis pigmentosa. Invest Ophthalmol Vis Sci 2011; 52: 4726–4733. [DOI] [PubMed] [Google Scholar]
- 82. Fujikado T, Kamei M, Sakaguchi H, et al. One-year outcome of 49-channel suprachoroidal-transretinal stimulation prosthesis in patients with advanced retinitis pigmentosa. Invest Ophthalmol Vis Sci 2016; 57: 6147–6157. [DOI] [PubMed] [Google Scholar]
- 83. Endo T, Fujikado T, Hirota M, et al. Light localization with low-contrast targets in a patient implanted with a suprachoroidal-transretinal stimulation retinal prosthesis. Graefes Arch Clin Exp Ophthalmol 2018; 48: 62–67. [DOI] [PubMed] [Google Scholar]
- 84. Haymes SA, Johnston AW, Heyes AD. Relationship between vision impairment and ability to perform activities of daily living. Ophthalmic Physiol Opt 2002; 22: 79–91. [DOI] [PubMed] [Google Scholar]
- 85. Szlyk JP. Relationship between difficulty in performing daily activities and clinical measures of visual function in patients with retinitis pigmentosa. Arch Ophthalmol 1997; 115: 53–59. [DOI] [PubMed] [Google Scholar]
- 86. Geruschat DR, Turano KA, Stahl JW. Traditional measures of mobility performance and retinitis pigmentosa. Optom Vis Sci 1998; 75: 525–537. [DOI] [PubMed] [Google Scholar]
- 87. Hazel CA, Petre KL, Armstrong RA, et al. Visual function and subjective quality of life compared in subjects with acquired macular disease. Invest Ophthalmol Vis Sci 2000; 41: 1309–1315. [PubMed] [Google Scholar]
- 88. Subhi H, Latham K, Myint J, et al. Functional visual fields: relationship of visual field areas to self-reported function. Ophthalmic Physiol Opt 2017; 37: 399–408. [DOI] [PubMed] [Google Scholar]
- 89. Pérez Fornos A, Sommerhalder J, Pittard A, et al. Simulation of artificial vision: IV. Visual information required to achieve simple pointing and manipulation tasks. Vision Res 2008; 48: 1705–1718. [DOI] [PubMed] [Google Scholar]
- 90. Sommerhalder J, Pérez Fornos A. Prospects and limitations of spatial resolution. In: Gabel VP. (ed.) Artificial vision. Cham: Springer, 2016, pp. 29–45. [Google Scholar]
- 91. Dagnelie G, Keane P, Narla V, et al. Real and virtual mobility performance in simulated prosthetic vision. J Neural Eng 2007; 4: S92–S101. [DOI] [PubMed] [Google Scholar]
- 92. Hayes JS, Yin VT, Piyathaisere D, et al. Visually guided performance of simple tasks using simulated prosthetic vision. Artif Organs 2003; 27: 1016–1028. [DOI] [PubMed] [Google Scholar]
- 93. Sommerhalder J, Rappaz B, de Haller R, et al. Simulation of artificial vision: II. Eccentric reading of full-page text and the learning of this task. Vision Res 2004; 44: 1693–1706. [DOI] [PubMed] [Google Scholar]
- 94. Dagnelie G. Psychophysical evaluation for visual prosthesis. Annu Rev Biomed Eng 2008; 10: 339–368. [DOI] [PubMed] [Google Scholar]
- 95. Bittner AK, Jeter P, Dagnelie G. Grating acuity and contrast tests for clinical trials of severe vision loss. Optom Vis Sci 2011; 88: 1153–1163. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96. Bach M, Wilke M, Wilhelm B, et al. Basic quantitative assessment of visual performance in patients with very low vision. Invest Ophthalmol Vis Sci 2010; 51: 1255–1260. [DOI] [PubMed] [Google Scholar]
- 97. Schulze-Bonsel K, Feltgen N, Burau H. Visual acuities ‘hand motion’ and ‘counting fingers’ can be quantified with the Freiburg Visual Acuity Test. Invest Ophthalmol Vis Sci 2006; 47: 1246–1240. [DOI] [PubMed] [Google Scholar]
- 98. Ruben G. Functional assessment of artificial vision. In: Gabel VP. (ed.) Artificial vision. Cham: Springer, 2016, pp. 9–19. [Google Scholar]
- 99. Gulati R, Roche H, Thayaparan K. The development of a picture discrimination test for people with very poor vision. Invest Ophthalmol Vis Sci 2011; 52: 1197. [Google Scholar]
- 100. Thompson RW, Barnett GD, Humayun MS, et al. Facial recognition using simulated prosthetic pixelized vision. Invest Ophthalmol Sci Vis 2003; 44: 5035–5042. [DOI] [PubMed] [Google Scholar]
- 101. Pérez Fornos A, Sommerhalder J, da Cruz L, et al. Temporal properties of visual perception on electrical stimulation of the retina. Invest Ophthalmol Vis Sci 2012; 53: 2720–2731. [DOI] [PubMed] [Google Scholar]
- 102. Zrenner E. Fighting blindness with microelectronics. Sci Transl Med 2013; 5: 210ps16. [DOI] [PubMed] [Google Scholar]
- 103. Nano Retina website. http://www.nano-retina.com/technology/#3dni (accessed 27 August 2018).
- 104. Prawer S, Garrett D. Laser microstructured diamond electrode arrays for bionic eye applications. In: Klotzbach U, Washio K, Kling R. (eds) Laser-based micro- and nanoprocessing XII, Vol. 10520, 2018, p. 10 New York: SPIE. [Google Scholar]
- 105. Jeong J, Shin S, Lee GJ, et al. Advancements in fabrication process of microelectrode array for a retinal prosthesis using Liquid Crystal Polymer (LCP). Conf Proc IEEE Eng Med Biol Soc 2013; 2013: 5295–5298. [DOI] [PubMed] [Google Scholar]
- 106. Diego G, Maria Rosa A, Maurizio M, et al. A polymer-based interface restores light sensitivity in blind rats. Front Neuroeng. Epub ahead of print 2014. DOI: 10.3389/conf.fneng.2014.11.00002. [DOI] [Google Scholar]
- 107. Maya-Vetencourt JF, Ghezzi D, Antognazza MR, et al. A fully organic retinal prosthesis restores vision in a rat model of degenerative blindness. Nat Mater 2017; 16: 681–689. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 108. Benfenati F, Lanzani G. New technologies for developing second generation retinal prostheses. Lab Anim (NY) 2018; 47: 71–75. [DOI] [PubMed] [Google Scholar]
- 109. Asher A, Segal WA, Baccus SA, et al. Image processing for a high-resolution optoelectronic retinal prosthesis. IEEE Trans Biomed Eng 2007; 54: 993–1004. [DOI] [PubMed] [Google Scholar]
- 110. Boyle JR. Region-of-interest processing for electronic visual prostheses. J Electron Imaging 2008; 17: 013002. [Google Scholar]
- 111. Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 1998; 20: 1254–1259. [Google Scholar]
- 112. Parikh N, Itti L, Weiland J. Saliency-based image processing for retinal prostheses. J Neural Eng 2010; 7: 016006. [DOI] [PubMed] [Google Scholar]
- 113. Feng C, Dai S, Zhao Y, et al. Edge-preserving image decomposition based on saliency map. In: 7th international congress on image and signal processing (CISP), Dalian, China, 14–16 October 2014, pp. 159–163. New York: IEEE. [Google Scholar]
- 114. Han T, Li H, Lyu Q, et al. Object recognition based on a foreground extraction method under simulated prosthetic vision. In: International symposium on bioelectronics and bioinformatics (ISBB), Beijing, China, 14–17 October 2015, pp. 172–175. New York: IEEE. [Google Scholar]
- 115. Parikh N, Itti L, Humayun M, et al. Performance of visually guided tasks using simulated prosthetic vision and saliency-based cues. J Neural Eng 2013; 10: 026017. [DOI] [PubMed] [Google Scholar]
- 116. Sahel J, Mohand-Said S, Stanga P, et al. Acuboost™: enhancing the maximum acuity of the Argus II Retinal Prosthesis System. Invest Ophthalmol Vis Sci 2013; 54: 1389. [Google Scholar]
- 117. Stanga P, Sahel J, Mohand-Said S, et al. Face detection using the Argus® II retinal prosthesis system. Invest Ophthalmol Vis Sci 2013; 54: 1766. [Google Scholar]
- 118. Zhao Y, Geng X, Li Q, et al. Recognition of a virtual scene via simulated prosthetic vision. Front Bioeng Biotechnol 2017; 5: 58. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 119. Beyeler M, Rokem A, Boynton GM, et al. Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies. J Neural Eng 2017; 14: 051003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 120. Chen SC, Suaning GJ, Morley JW, et al. Simulating prosthetic vision: II. Measuring functional capacity. Vision Res 2009; 49: 2329–2343. [DOI] [PubMed] [Google Scholar]


