Pedestrian Collision Detection and Avoidance in Cerebral Visual Impairment During Unrestricted Walking in an Immersive Virtual Reality Environment

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Walking safely through highly crowded environments is a significant challenge for individuals with cerebral visual impairment (CVI). Yet current ophthalmic examinations do not capture functional visual difficulties related to safe mobility. We developed an immersive virtual reality (VR)-based task that tracked eye gaze behaviors within dynamic areas of interest to assess pedestrian collision detection, avoidance, and associated visual scanning in CVI (n=12) compared to control (n=14) participants. Subjects walked through a simulated shopping mall populated with crowds of varying densities. The testing scenario was presented using a head-mounted display with integrated eye tracking, and locomotor, behavioral, and visual scanning responses were recorded. Compared to controls, CVI participants exhibited a slower mean preferred walking speed. They were also less likely and slower to detect target (colliding) pedestrians and were more likely to make a collision. CVI participants were also slower in making their first fixation and followed a larger visual scan path to find the target pedestrian. They also spent more time fixating on non-target compared to target pedestrians. Finally, CVI participants showed greater variability in their performance (including pathing deviations), reflecting a range of individual strategies, and maintained a larger walking safety margin (spatio-temporal envelope). These results provide objective evidence of mobility and associated gaze behaviors in CVI during navigation through highly crowded environments.

Authors

Jonathan Doyon (Harvard Medical School)
Madeleine Heynan (Harvard Medical School)
Wei Hay Lew (Harvard Medical School)
Alex D. Hwang (Harvard Medical School)
Lotfi B. Merabet (Harvard Medical School)

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