Autism spectrum disorder (ASD) 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 United States has been diagnosed with ASD.
What if someone invented a smartphone app that could help detect
autism spectrum disorder in children as young as two years old?
Could it lead to earlier detection and therefore better treatment?
‘A newly developed smartphone app can track eye movement to determine, in less than a minute, if a child is showing signs of autism spectrum disorder.’
A study co-authored by a University at Buffalo undergraduate and
presented at the IEEE Wireless Health conference at the National
Institutes of Health last month could provide the answer. It involves
the creation of an app for cell phones, tablets or computers that tracks
eye movement to determine, in less than a minute, if a child is showing
signs of autism spectrum disorder.
Early detection is important
Early detection of autism can dramatically improve the benefits
of treatment, but often the disability is not suspected until a child
"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, clinical assistant professor of pediatrics and
neurology at the Jacobs School of Medicine and Biomedical Sciences at
UB. Hartley-McAndrew, medical director of the Children's Guild
Foundation Autism Spectrum Disorder Center at Women & Children's
Hospital of Buffalo, is 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, an assistant professor in the Department of
Exceptional Education at SUNY Buffalo State College and 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
Young author, strong team
The principal author is Kun Woo Cho, an undergraduate majoring in
computer science and engineering. She worked with her research advisor
Wenyao Xu, assistant professor in the Department of Computer
Science and Engineering in UB's School of Engineering and Applied
Sciences. "This is an ongoing study on how to analyze ASD by monitoring
gaze patterns. I used the Wasserstein metric, designed the system
protocol, and visual stimuli using social scenes. This is teamwork, and I
learned from my advisor and graduate students in the lab," Cho said.
"On all the research work, we are working together."
Those lab co-workers and study co-authors are Feng Lin, research scientist, and Chen Song and Xiaowei Xu, students in UB's
Department of Computer Science and Engineering.
Eye tracking measurements
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%.
"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.
The study, entitled "Gaze-Wasserstein: A Quantitative Screening
Approach to Autism Spectrum Disorder," was one of the top-ranked papers
at the flagship Wireless Health conference this year, Xu said.
Social scenes elicit different gaze patterns
"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
"We speculate that it is due to their lack of ability to
interpret and understand the relationship depicted in the social scene,"
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.
Leading to a product
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.
Hartley-McAndrew said a lot of research is going into the use of
technology to help in detecting autism. "We still don't have a
completely objective measure to diagnose ASD. The diagnosis is based on
expert judgment. There are tests considered the 'gold standards,' but
they still are somewhat subjective," she said.
One benefit of the technology is that parents could use it at
home to determine if there is a need for clinical examination. And, she
said, the technology crosses cultural lines, and language is not a
"Nowadays, most people have a smartphone," she said.