Revolutionary video game identifies autism with 80% accuracy

Autism spectrum disorder (ASD) affects one in 36 children in the United States and one in 100 worldwide. Early diagnosis improves access to interventions that enhance quality of life. However, distinguishing ASD from other conditions like attention-deficit hyperactivity disorder (ADHD) remains a challenge.

ADHD co-occurs with ASD in 50% to 70% of cases, making diagnosis complex. Traditional methods rely on costly evaluations by highly trained professionals, often leading to delays or misdiagnoses.

Motor imitation plays a crucial role in social learning, with children learning behaviors by observing and mimicking others. Research shows that children with ASD struggle with imitation compared to neurotypical peers. Differences in motor skills have been documented in tasks such as ball-catching and coordination exercises.

Children with ASD tend to rely more on proprioceptive feedback—sensations from muscles and joints—rather than visual cues. These unique motor patterns suggest that imitation performance could serve as an effective biomarker for ASD.

Historically, assessing imitation has relied on human observation. Experts analyze how well a child replicates a movement, but this method has limitations. It is time-consuming, requires trained evaluators, and lacks precision. To improve the process, researchers have developed a technology-based solution: the Computerized Assessment of Motor Imitation (CAMI).

CAMI is a one-minute video game that uses motion-tracking technology to assess motor imitation. It eliminates the need for wearables or human observers, making it a more scalable and objective diagnostic tool. Developed by researchers at Kennedy Krieger Institute and Nottingham Trent University, the tool represents a breakthrough in autism diagnosis.

In a recent study involving 183 children aged 7–13, participants copied dance-like movements from a video avatar while CAMI analyzed their performance. The tool identified children with autism with 80% accuracy when compared to neurotypical peers. More importantly, it distinguished ASD from ADHD with 70% accuracy.

Since ASD and ADHD share overlapping traits, even experienced clinicians struggle to differentiate between them. The ability of CAMI to make this distinction marks a significant step forward.

Dr. Stewart Mostofsky, a pediatric neurologist and director at Kennedy Krieger Institute, emphasized the importance of accurate diagnosis. "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."

The current diagnostic process for ASD is often expensive and time-consuming. Families may spend between $1,500 and $3,000 annually on assessments. CAMI offers a faster, low-cost alternative that could revolutionize the field.

Dr. Bahar Tunçgenç, a social development expert at Nottingham Trent University, highlighted the significance of the tool. “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.”

Tunçgenç also emphasized CAMI’s ease of use. “What makes CAMI exciting is its simplicity. Video games are fun for kids, fast for clinicians, and provide clear results.”

Further refinements could expand CAMI’s applications to younger children and those with severe developmental challenges. If validated in broader populations, it could serve as a widely accessible diagnostic aid.

The potential of CAMI extends beyond autism. By improving diagnostic precision, researchers hope to refine assessments for other developmental conditions, such as developmental coordination disorder and language disorders. The tool’s ability to capture movement-based markers without relying on verbal communication makes it especially useful for nonverbal children.

“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.”

As technology continues to shape medical diagnostics, tools like CAMI offer hope for faster, more accurate assessments. By leveraging motion-tracking and computer vision, researchers are pioneering a new era in autism diagnosis—one that prioritizes accessibility, precision, and early intervention.

Note: Materials provided above by The Brighter Side of News. Content may be edited for style and length.

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