Using an Augmented Reality Device as a Distance-based Vision Aid—Promise and Limitations

SIGNIFICANCE For people with limited vision, wearable displays hold the potential to digitally enhance visual function. As these display technologies advance, it is important to understand their promise and limitations as vision aids. PURPOSE The aim of this study was to test the potential of a consumer augmented reality (AR) device for improving the functional vision of people with near-complete vision loss. METHODS An AR application that translates spatial information into high-contrast visual patterns was developed. Two experiments assessed the efficacy of the application to improve vision: an exploratory study with four visually impaired participants and a main controlled study with participants with simulated vision loss (n = 48). In both studies, performance was tested on a range of visual tasks (identifying the location, pose and gesture of a person, identifying objects, and moving around in an unfamiliar space). Participants' accuracy and confidence were compared on these tasks with and without augmented vision, as well as their subjective responses about ease of mobility. RESULTS In the main study, the AR application was associated with substantially improved accuracy and confidence in object recognition (all P < .001) and to a lesser degree in gesture recognition (P < .05). There was no significant change in performance on identifying body poses or in subjective assessments of mobility, as compared with a control group. CONCLUSIONS Consumer AR devices may soon be able to support applications that improve the functional vision of users for some tasks. In our study, both artificially impaired participants and participants with near-complete vision loss performed tasks that they could not do without the AR system. Current limitations in system performance and form factor, as well as the risk of overconfidence, will need to be overcome.

[1]  Shuihua Wang,et al.  RGB-D image-based detection of stairs, pedestrian crosswalks and traffic signs , 2014, J. Vis. Commun. Image Represent..

[2]  Yuhang Zhao,et al.  Understanding Low Vision People's Visual Perception on Commercial Augmented Reality Glasses , 2017, CHI.

[3]  R. Varma,et al.  Visual Impairment and Blindness in Adults in the United States: Demographic and Geographic Variations From 2015 to 2050. , 2016, JAMA ophthalmology.

[4]  Gordon E Legge,et al.  Identification and detection of simple 3D objects with severely blurred vision. , 2012, Investigative ophthalmology & visual science.

[5]  G. Rubin,et al.  Clinical performance of electronic, head‐mounted, low‐vision devices , 2004, Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians.

[6]  F. Vargas-Martin,et al.  Augmented-View for Restricted Visual Field: Multiple Device Implementations , 2002, Optometry and vision science : official publication of the American Academy of Optometry.

[7]  Christopher Kennard,et al.  Improving Mobility Performance in Low Vision With a Distance-Based Representation of the Visual Scene. , 2015, Investigative ophthalmology & visual science.

[8]  Douglas L. Rickman,et al.  Low vision enhancement system , 1994 .

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

[10]  J J van Rheede,et al.  A mobile image enhancement system for sight impaired individuals , 2016 .

[11]  Alexia Roux-Sibilon,et al.  Scene perception in age-related macular degeneration: Effect of spatial frequencies and contrast in residual vision , 2017, Vision Research.

[12]  Adam Finkelstein,et al.  Suggestive contours for conveying shape , 2003, ACM Trans. Graph..

[13]  Gordon E Legge,et al.  Seeing Steps and Ramps with Simulated Low Acuity: Impact of Texture and Locomotion , 2012, Optometry and vision science : official publication of the American Academy of Optometry.

[14]  Szymon Rusinkiewicz,et al.  Exaggerated shading for depicting shape and detail , 2006, ACM Trans. Graph..

[15]  Barry T. Thomas,et al.  Wearable Mobility Aid for Low Vision Using Scene Classification in a Markov Random Field Model Framework , 2003, Int. J. Hum. Comput. Interact..

[16]  Kenneth Knoblauch,et al.  Influence of background on image recognition in normal vision and age‐related macular degeneration , 2011, Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians.

[17]  ZhangChenyang,et al.  RGB-D image-based detection of stairs, pedestrian crosswalks and traffic signs , 2014 .

[18]  Ian Underwood,et al.  High Tech Aids Low Vision: A Review of Image Processing for the Visually Impaired. , 2015, Translational vision science & technology.

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

[20]  Susan M. Downes,et al.  A Depth-Based Head-Mounted Visual Display to Aid Navigation in Partially Sighted Individuals , 2013, PloS one.

[21]  Alex D. Hwang,et al.  An Augmented-Reality Edge Enhancement Application for Google Glass , 2014, Optometry and vision science : official publication of the American Academy of Optometry.

[22]  Robert W Massof,et al.  Psychometric properties of the Veterans Affairs Low-Vision Visual Functioning Questionnaire. , 2004, Investigative ophthalmology & visual science.

[23]  R W Massof,et al.  A Systems Model for Low Vision Rehabilitation. II. Measurement of Vision Disabilities , 1998, Optometry and vision science : official publication of the American Academy of Optometry.

[24]  Michael D. Crossland,et al.  Smartphone, tablet computer and e‐reader use by people with vision impairment , 2014, Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians.

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

[26]  M. Cowles Statistical Computing , 2004 .

[27]  Katherine E Henson,et al.  Risk of Suicide After Cancer Diagnosis in England , 2018, JAMA psychiatry.

[28]  J. Holmes,et al.  The effect of Bangerter filters on optotype acuity, Vernier acuity, and contrast sensitivity. , 2008, Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus.

[29]  E Peli,et al.  Vision Multiplexing: an Engineering Approach to Vision Rehabilitation Device Development , 2001, Optometry and vision science : official publication of the American Academy of Optometry.

[30]  Pascal Mamassian,et al.  Visual Confidence. , 2016, Annual review of vision science.

[31]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[32]  Barry T. Thomas,et al.  Head-Mounted Mobility Aid for Low Vision Using Scene Classification Techniques , 1998, Int. J. Virtual Real..