Vision function testing for a suprachoroidal retinal prosthesis: effects of image filtering

OBJECTIVE One strategy to improve the effectiveness of prosthetic vision devices is to process incoming images to ensure that key information can be perceived by the user. This paper presents the first comprehensive results of vision function testing for a suprachoroidal retinal prosthetic device utilizing of 20 stimulating electrodes. Further, we investigate whether using image filtering can improve results on a light localization task for implanted participants compared to minimal vision processing. No controlled implanted participant studies have yet investigated whether vision processing methods that are not task-specific can lead to improved results. APPROACH Three participants with profound vision loss from retinitis pigmentosa were implanted with a suprachoroidal retinal prosthesis. All three completed multiple trials of a light localization test, and one participant completed multiple trials of acuity tests. The visual representations used were: Lanczos2 (a high quality Nyquist bandlimited downsampling filter); minimal vision processing (MVP); wide view regional averaging filtering (WV); scrambled; and, system off. MAIN RESULTS Using Lanczos2, all three participants successfully completed a light localization task and obtained a significantly higher percentage of correct responses than using MVP ([Formula: see text]) or with system off ([Formula: see text]). Further, in a preliminary result using Lanczos2, one participant successfully completed grating acuity and Landolt C tasks, and showed significantly better performance ([Formula: see text]) compared to WV, scrambled and system off on the grating acuity task. SIGNIFICANCE Participants successfully completed vision tasks using a 20 electrode suprachoroidal retinal prosthesis. Vision processing with a Nyquist bandlimited image filter has shown an advantage for a light localization task. This result suggests that this and targeted, more advanced vision processing schemes may become important components of retinal prostheses to enhance performance. ClinicalTrials.gov Identifier: NCT01503576.

[1]  Patrick A. Tresco,et al.  Impedance characterization of microarray recording electrodes in vitro , 2005, IEEE Transactions on Biomedical Engineering.

[2]  Avi Caspi,et al.  Acuboost™: Enhancing the maximum acuity of the Argus II Retinal Prosthesis System , 2013 .

[3]  Jessy D. Dorn,et al.  Preliminary 6 month results from the argustm ii epiretinal prosthesis feasibility study , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  S C Chen,et al.  Visual acuity measurement of prosthetic vision: a virtual-reality simulation study , 2005, Journal of neural engineering.

[5]  Angelika Braun,et al.  Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS , 2013, Proceedings of the Royal Society B: Biological Sciences.

[6]  G. Medioni,et al.  Smart image processing system for retinal prosthesis , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[7]  E Peli,et al.  Image enhancement for the visually impaired: the effects of enhancement on face recognition. , 1994, Journal of the Optical Society of America. A, Optics, image science, and vision.

[8]  Farhad Hafezi,et al.  Temporal properties of visual perception on electrical stimulation of the retina. , 2012, Investigative ophthalmology & visual science.

[9]  Eli Peli,et al.  Image Enhancement For The Visually Impaired , 1984 .

[10]  E. Peli,et al.  Image enhancement for the visually impaired. Simulations and experimental results. , 1991, Investigative ophthalmology & visual science.

[11]  Daniel R Merrill,et al.  Impedance characterization of microarray recording electrodes in vitro , 2005, IEEE Trans. Biomed. Eng..

[12]  L. Ayton,et al.  Assessing residual visual function in severe vision loss. , 2014, Investigative ophthalmology & visual science.

[13]  Joel Villalobos,et al.  A wide-field suprachoroidal retinal prosthesis is stable and well tolerated following chronic implantation. , 2013, Investigative ophthalmology & visual science.

[14]  Richard A. Normann,et al.  Simulation of a phosphene-based visual field: Visual acuity in a pixelized vision system , 2006, Annals of Biomedical Engineering.

[15]  A Pentland,et al.  Maximum likelihood estimation: The best PEST , 1980, Perception & psychophysics.

[16]  Spencer C. Chen,et al.  Simulating prosthetic vision: I. Visual models of phosphenes , 2009, Vision Research.

[17]  Steven B. Smith,et al.  Digital Signal Processing: A Practical Guide for Engineers and Scientists , 2002 .

[18]  Max A. Viergever,et al.  Quantitative Comparison of Sinc-Approximating Kernels for Medical Image Interpolation , 1999, MICCAI.

[19]  Dirk Neumann,et al.  Neural Information Processing Efforts to Restore Vision in the Blind , 2004, ICONIP.

[20]  Takeo Kanade,et al.  Limits on super-resolution and how to break them , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[21]  Gislin Dagnelie,et al.  Facial recognition using simulated prosthetic pixelized vision. , 2003, Investigative ophthalmology & visual science.

[22]  R Clay Reid,et al.  Demonstration of artificial visual percepts generated through thalamic microstimulation , 2007, Proceedings of the National Academy of Sciences.

[23]  Alfred Stett,et al.  Subretinal electronic chips allow blind patients to read letters and combine them to words , 2010, Proceedings of the Royal Society B: Biological Sciences.

[24]  C. Veraart,et al.  Position, size and luminosity of phosphenes generated by direct optic nerve stimulation , 2003, Vision Research.

[25]  J. Rizzo.  Update on Retinal Prosthetic Research: The Boston Retinal Implant Project , 2011, Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society.

[26]  B. Sellhaus,et al.  Implantation and explantation of a wireless epiretinal retina implant device: observations during the EPIRET3 prospective clinical trial. , 2009, Investigative ophthalmology & visual science.

[27]  G.J. Suaning,et al.  Effect on prosthetic vision visual acuity by filtering schemes, filter cut-off frequency and phosphene matrix: a virtual reality simulation , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[28]  Hugh J. McDermott,et al.  Factors affecting perceptual thresholds in a suprachoroidal retinal prosthesis. , 2014, Investigative ophthalmology & visual science.

[29]  Jessy D. Dorn,et al.  The Detection of Motion by Blind Subjects With the Epiretinal 60-Electrode (Argus II) Retinal Prosthesis. , 2013, JAMA ophthalmology.

[30]  C. Duchon.  Lanczos Filtering in One and Two Dimensions , 1979 .

[31]  M. Bach,et al.  The Freiburg Visual Acuity test--automatic measurement of visual acuity. , 1996, Optometry and vision science : official publication of the American Academy of Optometry.

[32]  Avi Caspi,et al.  Face Detection using the Argus® II Retinal Prosthesis System , 2013 .

[33]  Nick Barnes,et al.  An face-based visual fixation system for prosthetic vision , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[34]  Nicholas L Opie,et al.  Development of a surgical procedure for implantation of a prototype suprachoroidal retinal prosthesis , 2014, Clinical & experimental ophthalmology.

[35]  Nick Barnes,et al.  Mobility and low contrast trip hazard avoidance using augmented depth , 2015, Journal of neural engineering.

[36]  Ken Turkowski,et al.  Filters for common resampling tasks , 1990 .

[37]  G. Brindley,et al.  The sensations produced by electrical stimulation of the visual cortex , 1968, The Journal of physiology.

[38]  Michael Bach,et al.  Basic quantitative assessment of visual performance in patients with very low vision. , 2010, Investigative ophthalmology & visual science.

[39]  W. Mokwa,et al.  Intraocular epiretinal prosthesis to restore vision in blind humans , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[40]  Arun N. Netravali,et al.  Reconstruction filters in computer-graphics , 1988, SIGGRAPH.

[41]  J. Weiland,et al.  Intraocular retinal prosthesis , 2006, IEEE Engineering in Medicine and Biology Magazine.

[42]  J. Weiland,et al.  Continuous electrical stimulation decreases retinal excitability but does not alter retinal morphology , 2011, Journal of neural engineering.

[43]  Gislin Dagnelie,et al.  Visually guided performance of simple tasks using simulated prosthetic vision. , 2003, Artificial organs.

[44]  N Parikh,et al.  Saliency-based image processing for retinal prostheses , 2010, Journal of neural engineering.

[45]  Nigel H. Lovell,et al.  Simulated prosthetic visual fixation, saccade, and smooth pursuit , 2005, Vision Research.

[46]  Paulette Lieby,et al.  Evaluating Lanczos2 Image Filtering for Visual Acuity In Simulated Prosthetic Vision , 2013 .

[47]  S. Kelly,et al.  Perceptual efficacy of electrical stimulation of human retina with a microelectrode array during short-term surgical trials. , 2003, Investigative ophthalmology & visual science.

[48]  Walid I Al-Atabany,et al.  Designing and testing scene enhancement algorithms for patients with retina degenerative disorders , 2010, Biomedical engineering online.

[49]  Nigel H. Lovell,et al.  Image Analysis for Microelectronic Retinal Prosthesis , 2008, IEEE Transactions on Biomedical Engineering.

[50]  Avi Caspi,et al.  Feasibility study of a retinal prosthesis: spatial vision with a 16-electrode implant. , 2009, Archives of ophthalmology.

[51]  Ione Fine,et al.  The Perceptual Effects of Chronic Retinal Stimulation , 2011 .

[52]  Jessy D. Dorn,et al.  Interim results from the international trial of Second Sight's visual prosthesis. , 2012, Ophthalmology.

[53]  Fivos Panetsos,et al.  Consistent Phosphenes Generated by Electrical Microstimulation of the Visual Thalamus. An Experimental Approach for Thalamic Visual Neuroprostheses , 2011, Front. Neurosci..

[54]  Gislin Dagnelie,et al.  Phosphene Mapping Techniques for Visual Prostheses , 2011 .

[55]  Christopher Fisher,et al.  Clinical Tests of Ultra-Low Vision Used to Evaluate Rudimentary Visual Perceptions Enabled by the BrainPort Vision Device. , 2013, Translational vision science & technology.

[56]  Gislin Dagnelie,et al.  Visual perception in a blind subject with a chronic microelectronic retinal prosthesis , 2003, Vision Research.

[57]  Chris E. Williams,et al.  First-in-Human Trial of a Novel Suprachoroidal Retinal Prosthesis , 2014, PloS one.

[58]  Gang Luo,et al.  Use of an augmented-vision device for visual search by patients with tunnel vision. , 2006, Investigative ophthalmology & visual science.

[59]  K. Horch,et al.  Mobility performance with a pixelized vision system , 1992, Vision Research.

[60]  Alex Fit-Florea,et al.  Precision and Performance: Floating Point and IEEE 754 Compliance for NVIDIA GPUs , 2011 .

[61]  Benoît Gérard,et al.  Pattern recognition with the optic nerve visual prosthesis. , 2003, Artificial organs.

[62]  Rolf Eckmiller,et al.  Tunable retina encoders for retina implants: why and how , 2005, Journal of neural engineering.

[63]  Hugh J. McDermott,et al.  neuroBi: A Highly Configurable Neurostimulator for a Retinal Prosthesis and Other Applications , 2015, IEEE Journal of Translational Engineering in Health and Medicine.

[64]  D. Dacey,et al.  Dendritic field size and morphology of midget and parasol ganglion cells of the human retina. , 1992, Proceedings of the National Academy of Sciences of the United States of America.