Influence of field of view in visual prostheses design: Analysis with a VR system

Sanchez-Garcia, M. (Universidad de Zaragoza) ; Martinez-Cantin, R. (Universidad de Zaragoza) ; Bermudez-Cameo, J. (Universidad de Zaragoza) ; Guerrero, J.J. (Universidad de Zaragoza)

Resumen: Objective.Visual prostheses are designed to restore partial functional vision in patients with total vision loss. Retinal visual prostheses provide limited capabilities as a result of low resolution, limited field of view and poor dynamic range. Understanding the influence of these parameters in the perception results can guide prostheses research and design.Approach.In this work, we evaluate the influence of field of view with respect to spatial resolution in visual prostheses, measuring the accuracy and response time in a search and recognition task. Twenty-four normally sighted participants were asked to find and recognize usual objects, such as furniture and home appliance in indoor room scenes. For the experiment, we use a new simulated prosthetic vision system that allows simple and effective experimentation. Our system uses a virtual-reality environment based on panoramic scenes. The simulator employs a head-mounted display which allows users to feel immersed in the scene by perceiving the entire scene all around. Our experiments use public image datasets and a commercial head-mounted display. We have also released the virtual-reality software for replicating and extending the experimentation.Main results.Results show that the accuracy and response time decrease when the field of view is increased. Furthermore, performance appears to be correlated with the angular resolution, but showing a diminishing return even with a resolution of less than 2.3 phosphenes per degree.Significance.Our results seem to indicate that, for the design of retinal prostheses, it is better to concentrate the phosphenes in a small area, to maximize the angular resolution, even if that implies sacrificing field of view.

Idioma: Inglés

DOI: 10.1088/1741-2552/abb9be

Año: 2020

Publicado en: Journal of Neural Engineering 17, 5 (2020), 056002 [14 pp]
ISSN: 1741-2560

Factor impacto JCR: 5.379 (2020)

Categ. JCR: NEUROSCIENCES rank: 66 / 273 = 0.242 (2020) - Q1 - T1
Categ. JCR: ENGINEERING, BIOMEDICAL rank: 20 / 89 = 0.225 (2020) - Q1 - T1

Factor impacto SCIMAGO: 1.594 - Cellular and Molecular Neuroscience (Q1) - Biomedical Engineering (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/BES-2016-078426
Financiación: info:eu-repo/grantAgreement/ES/MINECO/RTI2018-096903-B-I00

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)