Retina implant project : chronic implantation of active epiretinal implants

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Microcomputer-based artificial vision support system for real-time image processing for camera-driven visual prostheses

It is difficult to predict exactly what blind subjects with camera-driven visual prostheses (e.g., retinal implants) can perceive. Thus, it is prudent to offer them a wide variety of image processing filters and the capability to engage these filters repeatedly in any userdefined order to enhance their visual perception. To attain true portability, we employ a commercial off-the-shelf battery-powered general purpose Linux microprocessor platform to create the microcomputer-based artificial vision support system (µAVS^2) for real-time image processing. Truly standalone, µAVS^2 is smaller than a deck of playing cards, lightweight, fast, and equipped with USB, RS- 232 and Ethernet interfaces. Image processing filters on µAVS^2 operate in a user-defined linear sequential-loop fashion, resulting in vastly reduced memory and CPU requirements during execution. µAVS^2 imports raw video frames from a USB or IP camera, performs image processing, and issues the processed data over an outbound Internet TCP/IP or RS-232 connection to the visual prosthesis system. Hence, µAVS^2 affords users of current and future visual prostheses independent mobility and the capability to customize the visual perception generated. Additionally, µAVS^2 can easily be reconfigured for other prosthetic systems. Testing of µAVS^2 with actual retinal implant carriers is envisioned in the near future

Emerging technologies in artificial ocular devices: A systematic review

Background: Recent developments in vision restoration include visual prostheses designed to electrically stimulate artificial vision in those who have lost their sight. Major efforts in this area include multi-electrode arrays surgically implanted at various placement areas throughout the visual pathway. Visual prosthetic devices are named according to these placement areas (cortical, optic nerve, sub-retinal and epiretinal). These devices attempt to restore sight for retinal degenerative diseases such as Retinitis Pigmentosa (RP) and Age-related Macular Degeneration (AMD). Aim: To summarise the emerging technologies in the development of artificial ocular devices. Methods: The search methodology comprised seven databases for articles published between January 2000 and March 2017. Outcome data were analysed descriptively with results summarised in a Microsoft Excel database. Both quantitative and qualitative methodologies were used, and the main findings are discussed in a narrative format. Results: Eighty-nine full-text articles were included in this systematic review. Conclusion: The primary goal of these artificial devices is to provide functional vision in order to perform normal daily activities. Even though recent clinical trials in certain countries have shown advances in the development of various vision-restoring devices, they do not produce the same experience for the majority of patients and are unable to completely restore normal vision. The most common type of device according to its placement is the epiretinal device which is also the most successful device as determined in the majority of clinical trials

Zapping the Retina - Understanding electrical responsiveness and electrical desensitization in mouse retinal ganglion cells

The field of science and technology has come a long way since the famous 70’s science fiction series “The Six Million Dollar Man,” where a disabled pilot was transformed into a bionic superhero after receiving artificial implants. What was indeed once a science fiction has now turned into a science fact with the development of various electronic devices interfacing the human neurons in the brain, retina, and limbs. One such advancement was the development of retinal implants. Over the past two decades, the field of retinal prosthetics has made significant advancement in restoring functional vision in patients blinded by diseases such as Retinitis pigmentosa (RP) and Age-related macular degeneration (AMD). RP and AMD are the two leading cause of degenerative blindness. While there is still no definitive cure for either of these diseases, various treatment strategies are currently being explored. Of the various options, the most successful one has been the retinal implants. Retinal implants are small microelectrode or photodiode arrays, which are implanted in the eye of a patient, to stimulate the degenerating retina electrically. They are broadly classified into three types depending on the placement ̶ epiretinal (close proximity to retinal ganglion cells, RGCs) , subretinal (close proximity to bipolar cells, BP) and suprachoroidal (close proximity to choroid). While the ongoing human trials have shown promising results, there remains a considerable variability among patients concerning the quality of visual percepts which limits the working potential of these implants. One such limitation often reported by the implanted patients is “ fading” of visual percepts. Fading refers to the limited ability to elicit temporally stable visual percepts. While, this is not a primary concern for epiretinal implants , it is often observed in subretinal and suprachoroidal implants which use the remaining retinal network to control the temporal spiking pattern of the ganglion cells. The neural correlate of fading is often referred to as “electrical desensitization”, which is the reduction of ganglion cell responses to repetitive electrical stimulation . While much is known about the temporal component of desensitization ( time constant, τ), the spatial aspects (space constant, λ) has not been well characterized. Further, how both these aspects interact to generate spiking responses, remains poorly understood. These crucial questions formed the critical components of my thesis. To address these questions, we stimulated the retinal network electrically, with voltage and current pulses and recorded the corresponding spiking activity using the microelectrode arrays (MEAs). While addressing the primary question of my thesis, we were able to address few idiosyncrasies which has currently stymied the field of retinal prosthetics. At a conceptual level, we have developed an experimental and analysis framework by which one can identify the single stimulus that will activate the most ganglion cells (Chapter 2, Part 1). This stimulus is optimal for ‘blind’ experiments where the specific response properties of each cell are unknown. Furthermore, we attempted to understand the correspondence between the electrical response patterns and visual response types (Chapter 2, Part2). In Chapter 3, we sought to understand better how the visual responses parameters change during ongoing electrical stimulation. We demonstrated that apart from the adaptation occurring due to visual stimulation and invitro experimental conditions, the electrical stimulation alters the RGC visual responses, suggesting the requirement for stimulation-induced changes to be incorporated in the designing of stimulation paradigms for the implant. Finally addressing the primary question (Chapter 4) of my thesis with which we started, we were able to demonstrate, that the electrical desensitization requires the interaction of both time and distance and is not a global phenomenon of the retina. In the final chapter (Chapter 5) we summarize the results of the thesis, discuss the key outcomes and its relevance to the prosthetic field and other vision restoration strategies and the potential future directions of this research. Therefore, in future, to improve the efficacy of retinal prostheses and patient outcomes, it is crucial to have an in-depth understanding of the responsiveness of the retinal circuitry to electrical stimulation

The Argus II Retinal Prosthesis System

The field of retinal prosthetics has seen significant advances in the past 3 decades. Encouraging results from different groups have shown coarse objective functional improvement, using a range of technological and surgical approaches. The Argus II retinal prosthesis system was the first of its kind to receive regulatory approval for commercial use in Europe and the USA. The device is designed to replicate the function of photoreceptors in converting visual information into electrical neural signals in patients with profound visual loss secondary to degenerative retinal disease. Results from a phase II study of 30 patients have demonstrated improved performance in basic tests of visual function, object recognition, letter reading, prehension, orientation and mobility tasks. It is now the most widely implanted retinal prosthetic device worldwide. This chapter provides an overview of the requirements of a retinal prosthetic system, the results from the Argus II device to date, and an insight into some of the challenges and future directions of visually restorative therapies

Egocentric Computer Vision and Machine Learning for Simulated Prosthetic Vision

Las prótesis visuales actuales son capaces de proporcionar percepción visual a personas con cierta ceguera. Sin pasar por la parte dañada del camino visual, la estimulación eléctrica en la retina o en el sistema nervioso provoca percepciones puntuales conocidas como “fosfenos”. Debido a limitaciones fisiológicas y tecnológicas, la información que reciben los pacientes tiene una resolución muy baja y un campo de visión y rango dinámico reducido afectando seriamente la capacidad de la persona para reconocer y navegar en entornos desconocidos. En este contexto, la inclusión de nuevas técnicas de visión por computador es un tema clave activo y abierto. En esta tesis nos centramos especialmente en el problema de desarrollar técnicas para potenciar la información visual que recibe el paciente implantado y proponemos diferentes sistemas de visión protésica simulada para la experimentación.Primero, hemos combinado la salida de dos redes neuronales convolucionales para detectar bordes informativos estructurales y siluetas de objetos. Demostramos cómo se pueden reconocer rápidamente diferentes escenas y objetos incluso en las condiciones restringidas de la visión protésica. Nuestro método es muy adecuado para la comprensión de escenas de interiores comparado con los métodos tradicionales de procesamiento de imágenes utilizados en prótesis visuales.Segundo, presentamos un nuevo sistema de realidad virtual para entornos de visión protésica simulada más realistas usando escenas panorámicas, lo que nos permite estudiar sistemáticamente el rendimiento de la búsqueda y reconocimiento de objetos. Las escenas panorámicas permiten que los sujetos se sientan inmersos en la escena al percibir la escena completa (360 grados).En la tercera contribución demostramos cómo un sistema de navegación de realidad aumentada para visión protésica ayuda al rendimiento de la navegación al reducir el tiempo y la distancia para alcanzar los objetivos, incluso reduciendo significativamente el número de colisiones de obstáculos. Mediante el uso de un algoritmo de planificación de ruta, el sistema encamina al sujeto a través de una ruta más corta y sin obstáculos. Este trabajo está actualmente bajo revisión.En la cuarta contribución, evaluamos la agudeza visual midiendo la influencia del campo de visión con respecto a la resolución espacial en prótesis visuales a través de una pantalla montada en la cabeza. Para ello, usamos la visión protésica simulada en un entorno de realidad virtual para simular la experiencia de la vida real al usar una prótesis de retina. Este trabajo está actualmente bajo revisión.Finalmente, proponemos un modelo de Spiking Neural Network (SNN) que se basa en mecanismos biológicamente plausibles y utiliza un esquema de aprendizaje no supervisado para obtener mejores algoritmos computacionales y mejorar el rendimiento de las prótesis visuales actuales. El modelo SNN propuesto puede hacer uso de la señal de muestreo descendente de la unidad de procesamiento de información de las prótesis retinianas sin pasar por el análisis de imágenes retinianas, proporcionando información útil a los ciegos. Esté trabajo está actualmente en preparación.<br /

An Optoelectronic Stimulator for Retinal Prosthesis

Retinal prostheses require the presence of viable population of cells in the inner retina. Evaluations of retina with Age-Related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP) have shown a large number of cells remain in the inner retina compared with the outer retina. Therefore, vision loss caused by AMD and RP is potentially treatable with retinal prostheses. Photostimulation based retinal prostheses have shown many advantages compared with retinal implants. In contrary to electrode based stimulation, light does not require mechanical contact. Therefore, the system can be completely external and not does have the power and degradation problems of implanted devices. In addition, the stimulating point is flexible and does not require a prior decision on the stimulation location. Furthermore, a beam of light can be projected on tissue with both temporal and spatial precision. This thesis aims at fi nding a feasible solution to such a system. Firstly, a prototype of an optoelectronic stimulator was proposed and implemented by using the Xilinx Virtex-4 FPGA evaluation board. The platform was used to demonstrate the possibility of photostimulation of the photosensitized neurons. Meanwhile, with the aim of developing a portable retinal prosthesis, a system on chip (SoC) architecture was proposed and a wide tuning range sinusoidal voltage-controlled oscillator (VCO) which is the pivotal component of the system was designed. The VCO is based on a new designed Complementary Metal Oxide Semiconductor (CMOS) Operational Transconductance Ampli er (OTA) which achieves a good linearity over a wide tuning range. Both the OTA and the VCO were fabricated in the AMS 0.35 µm CMOS process. Finally a 9X9 CMOS image sensor with spiking pixels was designed. Each pixel acts as an independent oscillator whose frequency is controlled by the incident light intensity. The sensor was fabricated in the AMS 0.35 µm CMOS Opto Process. Experimental validation and measured results are provided