New App Detects Early Signs of Autism in Children

In just under a minute, a new smartphone app could potentially detect autism in a child as young as two years old.

The study, co-authored by University of Buffalo undergraduate student Kun Woo Cho and engineering professor Wenyao Xu, found that using a computer or tablet to track a child’s eye movements could reveal if he or she displays signs of autism spectrum disorder (ASD).

The app displays images with people and different social situations, and then tracks how the child’s eyes move around the picture. Children with autism typically look all over the picture, whereas kids without ASD are more focused.

“We speculate that it is due to their lack of ability to interpret and understand the relationship depicted in the social scene,” said Kun Woo Cho.

After testing the app on 32 children whose ages ranged from two to 10, they found that within 54 seconds they were able to determine if the child had ASD. The app had a rate of nearly 94 percent accuracy.

“The beauty of the mobile app is that it can be used by parents at home to assess the risk of whether a child may have ASD,” Professor Xu said in a statement. “This can allow families to seek therapy sooner and improve the benefits of treatment.”

According to the Centers for Disease Control and Prevention, one in 68 children is diagnosed with autism, with boys being over four times more likely than girls. However, autism is often not diagnosed until a child is in school.

Early detection of autism could lead to better, more effective treatments for the child.

“Although it’s never too late to start therapy, research demonstrates the earlier we diagnose, the better our outcomes,” said Dr. Kathy Ralabate Doody, a co-author of the study. “We offer many educational interventions to help children with autism reach the same developmental milestones met by children with typical development.”

Dr. Xu and Cho plan to test their app with another 300 to 400 children. They also plan to expand their study to see if the app is capable of detecting other neurological conditions, such as attention deficit disorder.

Danielle Tarasiuk

Danielle Tarasiuk is a multimedia journalist based in Los Angeles. Her work has been published on AllDay.com, Yahoo! Sports, KCET, and NPR-affiliate stations KPCC and KCRW. She’s a proud Sarah Lawrence College and USC Annenberg alumn.

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