Visual Attention Measures Predict Pedestrian Detection in Central Field Loss: A Pilot Study

Purpose The ability of visually impaired people to deploy attention effectively to maximize use of their residual vision in dynamic situations is fundamental to safe mobility. We conducted a pilot study to evaluate whether tests of dynamic attention (multiple object tracking; MOT) and static attention (Useful Field of View; UFOV) were predictive of the ability of people with central field loss (CFL) to detect pedestrian hazards in simulated driving. Methods 11 people with bilateral CFL (visual acuity 20/30-20/200) and 11 age-similar normally-sighted drivers participated. Dynamic and static attention were evaluated with brief, computer-based MOT and UFOV tasks, respectively. Dependent variables were the log speed threshold for 60% correct identification of targets (MOT) and the increase in the presentation duration for 75% correct identification of a central target when a concurrent peripheral task was added (UFOV divided and selective attention subtests). Participants drove in a simulator and pressed the horn whenever they detected pedestrians that walked or ran toward the road. The dependent variable was the proportion of timely reactions (could have stopped in time to avoid a collision). Results UFOV and MOT performance of CFL participants was poorer than that of controls, and the proportion of timely reactions was also lower (worse) (84% and 97%, respectively; p = 0.001). For CFL participants, higher proportions of timely reactions correlated significantly with higher (better) MOT speed thresholds (r = 0.73, p = 0.01), with better performance on the UFOV divided and selective attention subtests (r = −0.66 and −0.62, respectively, p<0.04), with better contrast sensitivity scores (r = 0.54, p = 0.08) and smaller scotomas (r = −0.60, p = 0.05). Conclusions Our results suggest that brief laboratory-based tests of visual attention may provide useful measures of functional visual ability of individuals with CFL relevant to more complex mobility tasks.

[1]  P. Vignal.  [Traffic safety]. , 1952, Gazette medicale de France.

[2]  C. Owsley,et al.  Driving Habits and Health-Related Quality of Life in Patients with Age-Related Maculopathy , 2003, Optometry and vision science : official publication of the American Academy of Optometry.

[3]  Eli Peli,et al.  Driving with hemianopia, I: Detection performance in a driving simulator. , 2009, Investigative Ophthalmology and Visual Science.

[4]  Cynthia Owsley Msph,et al.  Association Between Visual Attention and Mobility in Older Adults , 2004 .

[5]  B. J. Klevering,et al.  Eccentric Gaze Direction in Patients with Central Field Loss , 2011, Optometry and vision science : official publication of the American Academy of Optometry.

[6]  T. Kuyk,et al.  Visual factors and mobility in persons with age-related macular degeneration. , 1999, Journal of rehabilitation research and development.

[7]  B. J. Winer.  Statistical Principles in Experimental Design , 1992 .

[8]  Wiebo H Brouwer,et al.  Predicting Practical Fitness to Drive in Drivers With Visual Field Defects Caused by Ocular Pathology , 2004, Hum. Factors.

[9]  C. Owsley,et al.  Association Between Visual Attention and Mobility in Older Adults , 2004, Journal of the American Geriatrics Society.

[10]  Cynthia Owsley,et al.  Vision and driving , 2010, Vision Research.

[11]  R. Hogg,et al.  Visual function and dysfunction in early and late age-related maculopathy , 2006, Progress in Retinal and Eye Research.

[12]  Robert L. Mason,et al.  Statistical Principles in Experimental Design , 2003 .

[13]  Jan E Lovie-Kitchin,et al.  Visual Function, Visual Attention, and Mobility Performance in Low Vision , 2008, Optometry and vision science : official publication of the American Academy of Optometry.

[14]  A. Watson,et al.  Quest: A Bayesian adaptive psychometric method , 1983, Perception & psychophysics.

[15]  D. Roth,et al.  Cumulative Meta-analysis of the Relationship Between Useful Field of View and Driving Performance in Older Adults: Current and Future Implications , 2005, Optometry and vision science : official publication of the American Academy of Optometry.

[16]  L. A. Chiasson,et al.  Risk of falls and motor vehicle collisions in glaucoma. , 2007, Investigative ophthalmology & visual science.

[17]  J E Keeffe,et al.  Impact of age related macular degeneration on quality of life , 2006, British Journal of Ophthalmology.

[18]  Alex R. Bowers,et al.  Design for Simulator Performance Evaluations of Driving with Vision Impairments and Visual Aids , 2005 .

[19]  Alex R. Bowers,et al.  THE DESIGN OF DRIVING SIMULATOR PERFORMANCE EVALUATIONS FOR DRIVING WITH VISION IMPAIRMENTS AND VISUAL AIDS , 2005 .

[20]  Jonathan I. Flombaum,et al.  Attentional resources in visual tracking through occlusion: The high-beams effect , 2008, Cognition.

[21]  Karlene K. Ball,et al.  Reliability and Validity of Useful Field of View Test Scores as Administered by Personal Computer , 2005, Journal of clinical and experimental neuropsychology.

[22]  E. Peli,et al.  On-Road Driving with Moderate Visual Field Loss , 2005, Optometry and vision science : official publication of the American Academy of Optometry.

[23]  Ravi D. Patel,et al.  Review of Ranibizumab Trials for Neovascular Age-Related Macular Degeneration , 2011, Seminars in ophthalmology.

[24]  Eli Peli,et al.  Psychophysical contrast calibration , 2013, Vision Research.

[25]  Eli Peli,et al.  Hazard Detection by Drivers with Paracentral Homonymous Field Loss: A Small Case Series. , 2011, Journal of clinical & experimental ophthalmology.

[26]  Eli Peli,et al.  DLP-based dichoptic vision test system. , 2010, Journal of biomedical optics.

[27]  S. Emerson,et al.  AASHTO (American Association of State Highway and Transportation Officials). 2001. A Policy on Geometric Design of Highways and Streets. Fourth Edition. Washington, D.C. , 2007 .

[28]  Karlene K Ball,et al.  The useful field of view test: normative data for older adults. , 2006, Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists.

[29]  M. Grabowecky,et al.  Demand-based dynamic distribution of attention and monitoring of velocities during multiple-object tracking. , 2009, Journal of vision.

[30]  Eli Peli,et al.  Driving with hemianopia, II: lane position and steering in a driving simulator. , 2010, Investigative ophthalmology & visual science.

[31]  JAN E. LOVIE-KITCHIN,et al.  Vision and Mobility Performance of Subjects with Age-Related Macular Degeneration , 2002, Optometry and vision science : official publication of the American Academy of Optometry.

[32]  Gayla M. Cissell,et al.  Can High‐Risk Older Drivers Be Identified Through Performance‐Based Measures in a Department of Motor Vehicles Setting? , 2006, Journal of the American Geriatrics Society.

[33]  E Peli,et al.  Reading with a macular scotoma. II. Retinal locus for scanning text. , 1987, Investigative ophthalmology & visual science.

[34]  Z. Pylyshyn,et al.  Tracking Multiple Items Through Occlusion: Clues to Visual Objecthood , 1999, Cognitive Psychology.

[35]  E. Pfeiffer.  A Short Portable Mental Status Questionnaire for the Assessment of Organic Brain Deficit in Elderly Patients † , 1975, Journal of the American Geriatrics Society.

[36]  Eli Peli,et al.  Driving with central field loss I: effect of central scotomas on responses to hazards. , 2013, JAMA ophthalmology.

[37]  Z W Pylyshyn,et al.  Tracking multiple independent targets: evidence for a parallel tracking mechanism. , 1988, Spatial vision.