Smartphone App Shows Promise for Early Autism Detection

Emerging research suggests an app that tracks eye movements could determine, in less than a minute, if a child is showing signs of autism spectrum disorder (ASD).

The study, co-authored by a University at Buffalo undergraduate and presented at the IEEE Wireless Health conference in October, provides hope that the app for cell phones, tablets or computers will lead to early detection of ASD and therefore better treatment.

Clinicians explain that early detection of autism can dramatically improve the benefits of treatment, but often the disability is not suspected until a child enters school.

“The brain continues to grow and develop after birth. The earlier the diagnosis, the better. Then we can inform families and begin therapies which will improve symptoms and outcome,” said Michelle Hartley-McAndrew, M.D., a co-author of the study.

“Although it’s never too late to start therapy, research demonstrates the earlier we diagnose, the better our outcomes,” said Kathy Ralabate Doody, Ph.D., an assistant professor in the Department of Exceptional Education at SUNY Buffalo State College and a co-author as well.

“We offer many educational interventions to help children with autism reach the same developmental milestones met by children with typical development.”

The principal author is Kun Woo Cho, an undergraduate majoring in computer science and engineering. She worked with her research advisor Wenyao Xu, Ph.D., assistant professor in the Department of Computer Science and Engineering in University at Buffalo’s School of Engineering and Applied Sciences.

The app tracks eye movements of a child looking at pictures of social scenes; for example, those with multiple people. The eye movements of someone with ASD are often different from those of a person without autism. In the study, the app had an accuracy rating of 93.96 percent.

“Right now it is a prototype. We have to consider if other neurological conditions are included, like ADD, how that will affect the outcome,” Cho said.

Autism spectrum disorder affects one to two people per 1,000 worldwide. The Centers for Disease Control and Prevention reports that about one in 68 children in the U.S. has been diagnosed with ASD.

“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,” Xu said. “This can allow families to seek therapy sooner, and improve the benefits of treatment,” he said.

The study found that photos of social scenes evoke the most dramatic differences in eye movement between children with and without ASD. The eye tracking patterns of children with ASD looking at the photos are scattered, versus a more focused pattern of children without ASD.

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

Use of the app takes up to 54 seconds, which makes it less intrusive than other tests and valuable with children with short attention spans, Cho said.

The study included 32 children ranging in age from two to 10. Half of the children had been previously diagnosed with autism in accordance with DSM-V diagnostic criteria. The other half did not have ASD.

Further research will include expanding the study to another 300 to 400 children, which is about the annual enrollment for new evaluations at Children’s Guild Foundation Autism Spectrum Disorder Center at Women & Children’s Hospital of Buffalo.

Xu called the research “highly interdisciplinary” because of the need for computer technology, psychology for stimuli selection and medical expertise for the application of autism screening.

“This technology fills the gap between someone suffering from autism to diagnosis and treatment,” Xu said.

Source: University of Buffalo