Augmented and virtual reality approaches to help with peripheral vision loss

Peripheral vision loss (also called tunnel vision) is one of the main visual field disorders that can be very frustrating, and affect confidence and main activities of the patient. In this paper, two promising solutions for the peripheral vision loss are presented and discussed. The first one uses optical see-through glasses that are augmented by computer-generated images to notify the user about any moving parts the peripheral vision area. The second solution is to create a complete artificial reality scene and display it in the healthy area of the eye. In this case, the lost part of the vision is provided by: (i) augmenting the captured scenes (via built-in cameras) and (ii) generating an artificial image for the peripheral vision. For both scenarios, a unit of ubiquitous computing is proposed to process and present the captured images in a way tailored to individual needs of the patients. Technical requirements and psychological aspects of the proposed solutions are also presented and discussed in this paper.

[1]  Mari Ervasti,et al.  Touch- and audio-based medication management service concept for vision impaired older people , 2011, 2011 IEEE International Conference on RFID-Technologies and Applications.

[2]  Joyojeet Pal,et al.  : An Agenda for the ICTD Community , 2022 .

[3]  Christian Wallraven,et al.  Serial exploration of faces: comparing vision and touch. , 2012, Journal of vision.

[4]  R. Rosenholtz,et al.  A summary statistic representation in peripheral vision explains visual search. , 2009, Journal of vision.

[5]  Gretchen A. Stevens,et al.  Causes of vision loss worldwide, 1990-2010: a systematic analysis. , 2013, The Lancet. Global health.

[6]  Bruno Ando,et al.  Innovative Smart Sensing Solutions for the Visually Impaired , 2011 .

[7]  Matt Bower,et al.  What are the educational affordances of wearable technologies? , 2015, Comput. Educ..

[8]  Elizabeth A. Lahm,et al.  Implementation of Assistive Technology with Students who are Visually Impaired: Teachers’ Readiness , 2002 .

[9]  Luis A. Guerrero,et al.  An Indoor Navigation System for the Visually Impaired , 2012, Sensors.

[11]  Gérard G. Medioni,et al.  Robot vision for the visually impaired , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.

[12]  N. A. Bradley,et al.  Assistive Technology For Visually Impaired And Blind People , 2008 .

[13]  I. Rentschler,et al.  Peripheral vision and pattern recognition: a review. , 2011, Journal of vision.

[14]  J M J Roodhooft,et al.  Leading causes of blindness worldwide. , 2002, Bulletin de la Societe belge d'ophtalmologie.

[15]  S. Azen,et al.  Central and peripheral visual impairment and the risk of falls and falls with injury. , 2010, Ophthalmology.

[16]  Franco Tecchia Fundamentals of Wearable Computers and Augmented Reality, Second Edition , 2016, PRESENCE: Teleoperators and Virtual Environments.

[17]  Gbd Vleg Prevalence and causes of vision loss in high-income countries and in Eastern and Central Europe: 1990-2010. , 2014 .

[18]  M J Scherer,et al.  Outcomes of assistive technology use on quality of life. , 1996, Disability and rehabilitation.

[19]  Ramiro Velazquez,et al.  Wearable Assistive Devices for the Blind , 2016, ArXiv.