Imagine if we had a technology that made the diagnostic process for autism less stressful for children. Imagine if we combined it with existing manual methods so that it could help doctors better avoid a false positive autism diagnosis.
Recently, a study led by researchers in the Department of Applied Mathematics, characterized how children with autism spectrum disorder (ASD) scan a person’s face differently than a neuro-typical child. Those findings led to the development of a technique that considers how a child with ASD gaze transitions from one part of a person’s face to another. This will help doctors more quickly and accurately detect ASD in children.
“Many people are suffering from autism, and we need early diagnosis especially in children,” said Mehrshad Sadria, a master’s student in the applied mathematics department. “The current approaches to determining if someone has autism are not really child-friendly. Our method allows for the diagnosis to be made more easily and with less possibility of mistakes.
“The new technique can be used in all ASD diagnosis, but we believe it’s particularly effective for children.”
Currently, the two most favoured ways of assessing ASD involve a questionnaire or an evaluation from a psychologist. The researchers developed the new technique by:
- Evaluating 17 children with ASD and 23 neuro-typical children. The mean chronological ages of the ASD and neuro-typical groups were 5.5 and 4.8, respectively.
- Showing each participant 44 photographs of faces on a 19-inch screen, integrated into an eye-tracking system. The infrared device interpreted and identified the locations on the stimuli at which each child was looking via emission and reflection of wave from the iris.
- Separating the images into seven key areas of interest (AOIs) in which participants focussed their gaze: under the right eye, right eye, under the left eye, left eye, nose, mouth and other parts of the screen.
- Determining the time spent looking at each AOI, and also how they moved their eyes and scan the faces using four different concepts from network analysis to evaluate the varying degree of importance the children placed on the seven AOIs when exploring the facial features.
“It is much easier for children to just look at something, like the animated face of a dog, than to fill out a questionnaire or be evaluated by a psychologist,” said Anita Layton, who supervises Sadria and is a professor of Applied Mathematics, Pharmacy and Biology at Waterloo. “Also, the challenge many psychologists face is that sometimes behaviours deteriorate over time, so the child might not display signs of autism, but then a few years later, something starts showing up.
“Our technique is not just about behaviour or whether a child is focussing on the mouth or eyes. It’s about how a child looks at everything.”