3D face photos could be a sleep apnea screening tool - Neuroscience News

Summary: Using 3D imaging and artificial intelligence, researchers discovered the shortest distance between two points on the curved surface of the face predicted, with 89% accuracy, which patients had sleep apnea. Facial features analyzed from 3D photographs could predict the likelihood of having obstructive sleep apnea, according to a study published in the April issue of the Journal of Clinical Sleep Medicine. Using 3D photography, the study found that geodesic measurements -- the shortest distance between two points on a curved surface -- predicted with 89 percent accuracy which patients had sleep apnea. Using traditional 2D linear measurements alone, the algorithm's accuracy was 86 percent. "This application of the technique used predetermined landmarks on the face and neck," said principle investigator Peter Eastwood, who holds a doctorate in respiratory and sleep physiology and is the director of the Centre for Sleep Science at the University of Western Australia (UWA).