In the recent years, diagnosing an autism child has been a difficult process. There have been only a test to detect the disorder, and current screening methods tend to rely on analyzing a child’s behavior.
The researchers of Rutgers University and Indiana University have developed a new tool, which can be used to both diagnose and treat children with autism. The new method much more focuses on quality movement.
The new technique uses sensors to analyze an involuntary movements and motor functions in relation to cognitive development. According to the researchers, it is the first diagnostic method for autism to use quantitative criteria. Researchers have detailed their therapeutic tool, helping autistic children learn and communicate more effectively.
Dr. Elizabeth Torres, a computational neuroscientist at Rutgers University told “It gives us a fingerprint of that person we can measure their patterns and measure the change and rate of change. It is in the rate of change of this pattern that the (autism) mystery lies.”
Torres teamed up with fellow Rutgers colleague Dimitri Metaxas and Jorge Jose, a neuroscientist at Indiana University, to develop their novel sensory screening technique. Using a motion capture system, the researchers place sensors on an autistic patient’s body that take up to 240 measurements per second. They then analyze those movements with a new statistical computer program they have developed.
This method records a patient’s involuntary movements that are unconscious and controlled by the peripheral nervous system. According to Torres, the voluntary movements of children with autism are exponentially different and too extreme to be measured. However, when it comes to involuntary movements, autistic children are still different but similar enough so that their unconscious movements can be measured with a newly developed set of probability distributions.
The team used this method on 78 children and adults with autism, including those with mild forms of the disorder and autistic children who were nonverbal and low-functioning. According to the researchers, the screening technique correctly diagnosed the patients every time, and it could even classify different subtypes, identify gender differences and track an individual’s progress through treatment.
According to Torres, it’s the element of self-discovery and internal motivation that makes their therapy more successful than current treatment options, which focus on conditioning children to perform socially acceptable behavior – rather than having them figure it out on their own