Researchers at Duke University created a robotic eye scanner that can detect signs of various eye diseases, including glaucoma and diabetic retinopathy. The system includes several 3D cameras that track the patient’s location, which only needs to be placed in front of the robot, while a robotic arm containing the scanning hardware tracks and analyzes the patient’s eyes. In less than a minute, the system produces images as clear as those obtained by the technologies currently in use, which require a patient to use a headrest and chin to prevent any movement of the head.
Currently, highly trained technicians can identify various eye diseases using optical coherence tomography (OCT), which typically requires a large desktop system. This technique also requires the patient to fix their head on a stationary support for the head and chin, to ensure that it does not move and interfere with eye examination. The scan itself involves shining a beam of light into the eye and then analyzing the reflected light to infer the presence of various diseases, such as age-related macular degeneration, glaucoma, and diabetic retinopathy.
These systems work well, but in the COVID era many would prefer not to share the head and chin with the rest of the patients. In addition, the skilled technicians needed to operate these scanners may be scarce, which is part of the motivation for this new system.
“Not everywhere is there a resource like the Duke Eye Center, where we have access to these highly trained and specialized technicians like ophthalmic photographers,” said Ryan McNabb, a researcher involved in the study. “But with our new tool, you won’t need advanced training to use it. We are optimistic that something like this can be easily used in places like optometry clinics, primary care clinics or even emergency departments. OCT is a useful diagnostic tool, and such advances facilitate access to wider communities. ”
The heart of the system is a robotic arm, which is guided by two 3D cameras that identify where the patient is. The robotic arm quickly scans the patient’s eyes, taking less than a minute to scan both, but makes no physical contact with the patient during the scan. “The robotic arm gives us the flexibility of hand-held OCT scanners, but we don’t have to worry about any operator shaking,” said Mark Draelos, another researcher involved in the study. “If a person moves, the robot moves with it. As long as the scanner is aligned an inch from where it should be in your pupil, the scanner can get an image as good as a desktop scanner.
“While this is a solution to image collection problems, we believe it will combine incredibly well with recent advances in machine learning for interpreting OCT images,” McNabb said. “We really bring TCA to patients instead of limiting these tools to specialized clinics and I think it will make it much easier to help a wider population of people.”
Watch a video of the new robot in action at this link.
Study a Biomedical Engineering of Nature: Non-contact optical coherence tomography of the eyes of independent people with a robotic scanner