April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Mobility performance in low vision: Capturing the dynamics of target finding and obstacle avoidance across different tasks
Author Affiliations & Notes
  • Joram Jacob van Rheede
    Nuffield Dept. of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
  • Iain Wilson
    Nuffield Dept. of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
  • Rose I Qian
    Nuffield Dept. of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
  • Stuart Golodetz
    Nuffield Dept. of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
  • Susan M Downes
    Nuffield Department of Ophthalmology, University of Oxford, Oxford, United Kingdom
    Oxford Eye Hospital, University of Oxford, Oxford, United Kingdom
  • Robert E MacLaren
    Nuffield Department of Ophthalmology, University of Oxford, Oxford, United Kingdom
    Oxford Eye Hospital, University of Oxford, Oxford, United Kingdom
  • Christopher Kennard
    Nuffield Dept. of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
  • Stephen Lloyd Hicks
    Nuffield Dept. of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
  • Footnotes
    Commercial Relationships Joram van Rheede, None; Iain Wilson, None; Rose Qian, None; Stuart Golodetz, None; Susan Downes, None; Robert MacLaren, None; Christopher Kennard, None; Stephen Hicks, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 4127. doi:
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      Joram Jacob van Rheede, Iain Wilson, Rose I Qian, Stuart Golodetz, Susan M Downes, Robert E MacLaren, Christopher Kennard, Stephen Lloyd Hicks; Mobility performance in low vision: Capturing the dynamics of target finding and obstacle avoidance across different tasks. Invest. Ophthalmol. Vis. Sci. 2014;55(13):4127.

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      © 2017 Association for Research in Vision and Ophthalmology.

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Abstract
 
Purpose
 

Recent developments in visual prosthesis and assistive technology research have increased the need for accurate visual mobility performance (VMP) measures in low vision (LV). Current approaches are based on the time participants take to follow a set course, overall walking speed, and the number of collisions. These measures do not generalise well across experimental setups, and do not capture the dynamics of VMP, which may provide useful information about the nature of visual constraints on mobility. We aim to address these issues by developing measures to dynamically assess VMP that generalise across different tasks, that do not require participants to follow a set course, and that are sensitive enough to differentiate between performance with and without assistive technology.

 
Methods
 

12 LV and 4 control participants performed target finding and obstacle avoidance tasks in a custom VMP assessment facility. We used cameras to track the position of participants in relation to obstacles and targets over time, and compared VMP with and without residual vision glasses (RVGs), a new assistive technology for LV.

 
Results
 

We report that dynamic measures of walking behaviour provide more information about VMP than aggregate measures. Taking into account walking speed as a function of proximity to objects and targets and the heading direction of participants, it was possible to extract simple measures that reflect different aspects of VMP (see Figures). These measures could differentiate between LV and control participants, were able to quantify differences in VMP with and without RVGs, and did not require participants to follow a set course.

 
Conclusions
 

Current strategies for quantifying VMP can be improved upon by tracking the position of participants in relation to targets and obstacles over time to capture the dynamics of walking behaviour. This information can be used to generate simple output measures that can be generalised across tasks, and that are sensitive enough to differentiate between LV patients, monitor VMP over time, and investigate the potential benefit of assistive technology.

 
 
Path of a subject for an obstacle avoidance task (top) and observed walking speed (bottom). Arrows indicate obstacle-related velocity adjustments.
 
Path of a subject for an obstacle avoidance task (top) and observed walking speed (bottom). Arrows indicate obstacle-related velocity adjustments.
 
 
The point at which a subject begins to deviate from an obstacle provides a readout of obstacle awareness.
 
The point at which a subject begins to deviate from an obstacle provides a readout of obstacle awareness.
 
Keywords: 584 low vision • 717 space and scene perception • 753 vision and action  
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