A new one-minute video game is able to accurately and efficiently identify children with autism from those who have ADHD or are neurotypical.

Developed by researchers at Kennedy Krieger Institute and Nottingham Trent University, the tool, called the Computerized Assessment of Motor Imitation (CAMI), uses motion-tracking technology to detect differences in motor imitation skills.

In the study, 183 children, ages 7-13, were asked to copy the dance-like movements of a video avatar for one minute, while their imitation performance was measured using CAMI. The video game tool was able to correctly distinguish children with autism vs. neurotypical children with a 80% success rate. CAMI also differentiated autism from ADHD with 70% accuracy. Researchers say that this is a particular challenge because ADHD and autism often co-occur, and it can be hard to identify the diagnoses, even by expert clinicians.

Dr. Stewart Mostofsky, a pediatric neurologist and director of the Center for Neurodevelopmental and Imaging Research at Kennedy Krieger Institute and co-author of the study, says this tool is a step forward in how we diagnose autism.

“Diagnosing autism can be challenging, especially when children have overlapping traits with other conditions like ADHD. If the condition is misdiagnosed, it can impact support and resources for the child.” said Dr. Mostofsky.

It is often time-consuming to diagnose autism, requiring highly trained clinicians and costing families an estimated $1,500 to $3,000 annually, according to the U.S. National Library of Medicine.

Dr. Bahar Tunçgenç, senior author and social development expert at Nottingham Trent University, said: “Autism is traditionally seen as a social-communication disorder, but we now know sensory-motor difficulties, like motor imitation, play a key role in shaping social and communication skills. CAMI identifies autism by tapping into these challenges, which are distinct from ADHD.” She added, “What makes CAMI exciting is its simplicity. Video games are fun for kids, fast for clinicians, and provide clear results.”

With further development, CAMI could be adapted for younger children and those with more severe developmental challenges, broadening its impact. Researchers hope CAMI’s success inspires new ways to simplify and improve diagnostic tools for other conditions.

“This tool could transform autism diagnoses worldwide,” said. Dr. Mostofsky. “By identifying autism as precisely as possible, we can connect children to interventions that improve their quality of life and long-term outcomes. We want to see CAMI used widely in clinics to support diagnosis as an alternative that is quick, low-cost, and requires minimal set-up.”



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