Researchers report new wearable device reduces collisions and falls in those who are visually impaired by 37%.
A study published by JAMA Ophthalmology found that a wearable computer vision device may help reduce collisions and other accidents in the blind and visually impaired,
When used in combination with a long cane or guide dog, the technology, which detects nearby movement and objects with an on-board camera, reduced the risk for collisions and falls by nearly 40% compared with other mobility aids, the data showed.
“Independent travel is an essential part of daily life for many people who are visually impaired, but they face a greater risk of bumping into obstacles when they walk on their own,” study co-author Gang Luo said in a press release.
“Many blind individuals use long canes to detect obstacles [and] collision risks are not completely eliminated. We sought to develop … a device that can augment these everyday mobility aids, further improving their safety,” said Luo, an associate professor of ophthalmology at Harvard Medical School in Cambridge, Mass.
Those who are visually impaired are at increased risk for collisions and falls, even with mobility aids such as long canes and guide dogs, according to Prevent Blindness.
Long canes are among the most effective and affordable mobility tools for a person who is blind or visually impaired but they can only detect hazards on the ground that are within reach and often miss hazards above ground level, the organization says.
Guide dogs also are highly effective, but are in short supply and can cost up to $60,000, it says.
What is included in the device?
The device developed by Luo and his colleagues features a data recording unit enclosed in a sling backpack with a chest-mounted, wide-angle camera on the strap and two Bluetooth-connected wristbands worn by the user.
How does it work?
The camera is connected to a processing unit that records images and analyzes any collision risk based on the movement of incoming and surrounding objects in the camera’s field of view, the researchers said.
If there is a risk for collision on a user’s left or right side, the corresponding wristband will vibrate, while a potential head-on collision will cause both wristbands to vibrate.
The device is designed to warn users only of approaching obstacles that pose a collision risk and ignore objects not on a collision course, they said.
What were some of the results from the study?
For this study, Luo and his colleagues tested the device on 31 blind and visually impaired adults who use a long cane or guide dog, or both, to aid their daily mobility.
After being trained to use the device, participants wore it for about a month during daily activities, while continuing with their usual mobility device.
The device was randomized to switch between active mode, in which the users could receive vibrating alerts for imminent collisions, and silent mode, in which the device still processed and recorded images, but did not give users a warning.
The silent mode is equivalent to the placebo condition in many clinical trials testing drugs, so the wearers and researchers would not know when the device modes changed during the testing.
The effectiveness of the device was measured by comparing collision incidents that occurred during active and silent modes. There were 37% fewer collisions in the former than in the latter.
Are there any plans to market the device to the public?
The researchers hope to leverage improvements in digital processing and camera technology to make their device smaller and more cosmetically appealing before applying to the U.S. Food and Drug Administration for approval.
“Long canes are still very helpful and cost-effective tools that work well in many situations, but we hope a wearable device like this can fill in the gaps that the cane might miss, providing a more affordable, easier to obtain option than a guide dog,” study co-author Alex Bowers said in a press release.
In addition, “the insights provided by our data can be valuable for improving mobility aid training,” said Bowers, an associate professor of ophthalmology at Harvard Medical School.
