Structured Laser Light Improves Tripping Hazard Recognition for People with Visual Impairments.

Abstract

Purpose:

Using a geometrically derived model and a virtual curb simulator, we quantify the degree to which a wearable device that projects a laser line onto tripping hazards in a pedestrian's path improves visual recognition for people with visual impairments (VI). We confirm this with subjects' performance on computer simulations of low contrast curbs.

Methods:

We derive geometric expressions quantifying the visual cue users perceive when a single laser line is projected from their hip onto a curb. We show how the efficacy of this cue changes with the angle of the laser line relative to the subject's walking trajectory. We confirm this result with data from three subjects with VI in a simulated curb recognition task in which subjects classified computer images as an "Ascending," "Flat," or "Descending" curb.

Results:

The derived model predicts that human recognition performance depends strongly on the laser line angle and the subject data confirms this (r2 = 0.86,P < 0.001). The laser line cue improved subject accuracy from a chance level of 33% to 95% for a simulated, one-inch, low-contrast curb at a distance of five feet.

Conclusions:

Recognition of curbs in low light can be improved by augmenting the scene with a single laser line projected from a user's hip, if the angle of laser line is appropriately selected.

Translational Relevance:

A majority of people with VI rely on their impaired residual vision for mobility, rather than a mobility aid, resulting in increased injury for this population. Enhancing residual vision could promote safety, increase independence, and reduce medical costs.

• Authors: Michael Stahl, Eli Peli
• Journal: Translational vision science & technology (Transl Vis Sci Technol) Vol. 9 Issue 9 Pg. 6 (08 2020) ISSN: 2164-2591 [Print] United States
• PMID: 32884857 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)
• Copyright: Copyright 2020 The Authors.

Topics

• Computer Simulation
• Humans
• Light
• Vision Disorders
• Walking
• Wearable Electronic Devices