A novel use of movement tracking has provided a way to diagnose autism in children as young as three years old, as documented by new research from Indiana University’s School of Medicine and Rutgers University. This quantitative evaluation for autism offers and objective assessment of a subject’s movement patterns and could lead to earlier diagnosis and intervention for children with autism.
The research, funded by a $670,000 grant from the National Science Foundation, uses a computer program that is able to take 240 images per second. The program measures the minutia of the subject’s movements and determines the level of deviation from typical movement patterns. Using this data, the program creates a profile from the subject’s unique systematic signature. Finally, it uses the profile to evaluate whether the subject has autism and it can even diagnose subtypes of autism and identify gender differences.
“This research may open doors for the autistic community by offering the option of a dynamic diagnosis at a much earlier age and possibly enabling the start of therapy sooner in the child’s development,” explained Dr. Jorge V. José, vice president of research and professor of cellular and integrative physiology at Indiana University. Another benefit of this form of diagnosis is that it enables non-verbal children to obtain an evidence-based diagnosis.
In addition to diagnosing autism, this technology makes it possible to estimate a person’s cognitive abilities merely by measuring the variability in his or her movements. According to Dr. José, this could lead to a way to develop therapies for young autistic children.
This study is published in the open-access journal Frontiers in Neuroscience.
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