Research from Scotland's University of Strathclyde, led by Jonathan Delafield-Butt, PhD, has investigated a new way to diagnose autism by tracking the participants' hand movements while playing games on an iPad. The new method may offer a patient-friendly means of detecting the disease in children.

"We have shown that children with autism can be identified by their gameplay patterns on an iPad,” said Delafield-Butt in a statement. "This is potentially a major breakthrough for early identification of autism, because no stressful and expensive tests by clinicians are needed. Early detection is important as this can allow parents and children to gain access to a range of services support.

Analyzing 37 autistic children ages three to six, researchers had the patients play games on an iPad enabled with a touch-sensitive screen and movement sensors. Collecting the data from the hand movements of the patients while playing games revealed that the movement patterns were key in diagnosing autism.

"In other words, it is not social, emotional or cognitive aspects of the gameplay that identify autism. Rather, the key difference is in the way children with autism move their hands as they touch, swipe, and gesture with the iPad during the game,” wrote Delafield-Butt. "These data support the notion disruption to movement is a core feature of autism and demonstrate autism can be computationally assessed by fun, smart device gameplay."