A video game that can identify children with autism with 80% accuracy has been released
Autism is known as a developmental disorder that causes difficulties in interpersonal relationships, but it is also related to the motor function of imitating other people's body language and facial expressions, and it is becoming clear that this is also a cause of communication disorders. Applying this knowledge, a paper was published on a technology that can identify autism with high accuracy by tracing the movements of children enjoying a dance game.
Innovative one-minute video game boasts 80% success rate in diagnosing autism | Nottingham Trent University
https://www.ntu.ac.uk/about-us/news/news-articles/2025/01/one-minute-video-game-to-diagnose-autism
The Computer Assisted Motor Imitation (CAMI) test, developed jointly by researchers at Nottingham Trent University in the UK and the Kennedy Krieger Institute in the US, is a tool that uses motion tracking technology to monitor children's motor imitation skills and identify autism with high accuracy.
You can see children actually playing with CAMI below.
Computerized Assessment of Motor Imitation (CAMI) in action. - YouTube
An avatar appears on the TV screen performing dance-like movements, and children imitate the movements by moving their arms and legs.
The basic principle of CAMI is that the child's movements are recorded and analyzed using Kinect sensors placed above the monitor and behind the child.
Early diagnosis and effective intervention can improve the quality of life of individuals with autism, but diagnosis requires time and advanced expertise, and reliable, cost-effective testing methods have yet to be established. In particular, it is said that even specialized clinicians have difficulty distinguishing autism from attention-deficit hyperactivity disorder (ADHD), which often occurs concomitantly.
Rather than focusing on traditional diagnostic approaches that focus on communication disorders, the team focused on the difficulties that autistic people have when trying to imitate human behavior. Using computer vision technology, they developed CAMI, a game-based tool that can diagnose autism in children without the need for wearable devices that restrict a child's movement or manual data entry.
To test the accuracy of CAMI, the team recruited 183 children aged 7 to 13 years old from four groups: those with ADHD but not autism, those with autism and ADHD, those with autism but not ADHD, and those with typical development . They were asked to imitate the movements of an avatar shown on television for one minute, and their movements were measured using CAMI.
The results of this test showed that CAMI could correctly identify children with autism from typically developing children with 80% accuracy, and more importantly, it could also distinguish between autism and ADHD with 70% accuracy.
'The appeal of CAMI is its simplicity,' said Bahar Tunçgenç, a researcher in the School of Psychology at Nottingham Trent University and lead author of the paper. 'Video games are hugely popular with children, so CAMI allows us to get quick results that are fun for children and easy for clinicians to interpret. My hope is that CAMI will eventually be used in all clinical settings.'
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