AI Breakthrough in Autism Detection Through Simple Hand Movements

AI is, by and large, a controversial yet fascinating technological development that is evolving every day. However, it cannot be denied that even at this early stage of AI development, the technology has already provided us with significant benefits, prompting researchers to continue improving it.

One sector where AI has proven beneficial is the medical field, where its impact on medical technologies has been positively demonstrated. A study conducted at York University found that AI may hold the key to early detection of autism, simply by analyzing how we grasp everyday objects between our fingers.

The researchers, along with their collaborators, used motion-tracking sensors to collect grasping behavior data from a group of 59 young adults. Each participant was asked to pick up various rectangular objects using only their thumb and index finger.

From these movements, the researchers collected over a dozen motor control features, including finger speed, hand trajectory, and more. These data were then fed into five different machine learning models, and the AI was able to detect autism in individuals with 89% accuracy.

While these findings require further research, they suggest that autism is not solely a social and behavioral condition, but may also involve motor coordination that can be measured. The researchers also hope to expand the capabilities of AI to eventually identify different types of autism or make the technology available in schools and pediatric clinics.