Researchers from the University of Buffalo have develop a new app for smartphones, tablets, or computers that is capable of detecting early signs of autism spectrum disorder (ASD) in less than a minute.
The new app, described in a paper presented at the IEEE Wireless Health Conference, works by tracking the eye movement of a child looking at pictures of social scenes. The researchers noted that the eye movement of a child with autism spectrum disorder may differ from a child without ASD.
"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," explained Kun Woo Cho, an undergraduate majoring in computer science and engineering and principal author of the study, in a statement.
In a study participated by 32 children, the app had an accuracy rating of 93.96 percent. Half of the children in the study have been previously diagnosed with ASD in accordance with DSM-V diagnostic criteria, while the other half did not have ASD.
Using the app, which only took about 54 seconds, the researchers were able to determine that photos with social scenes evoke the most dramatic differences in eye movement between children with and without ASD. The researchers observed that the eye tracking pattern of children with ASD looking at the photos are scattered. On the other hand, children without ASD have more focused eye tracking pattern. The researchers speculate that the inability of the children with ASD to interpret and understand the relationship depicted in the social scenes is responsible for the difference in the eye tracking pattern of children with ASD and those without.
According to a press release, 1 to 2 people worldwide are affected by ASD. In the United States, about 1 in 68 children has been diagnosed with ASD. With early detection of the disorder, the researchers believe that children diagnosed with ASD could receive better benefits from early treatments.
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