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For decades, diagnosing a child with autism has been a difficult process. There are no medical tests capable of detecting the disorder, and current screening methods tend to rely solely on analyzing a child’s behavior.
But now, researchers from Rutgers University and Indiana University have developed a brand new screening tool, which can be used to both diagnose and treat children with autism. The new method focuses on measuring a much more objective quality: movement.
The new technique uses a series of sensors to analyze an individual’s involuntary movements and motor functions in relation to his or her cognitive development. According to the researchers, it is the first diagnostic method for autism to use quantitative criteria. Researchers have detailed how their work could potentially be used as an early therapeutic tool, helping autistic children learn and communicate more effectively.
“Our contribution is this statistical platform we created, which is tailored to each person,” Dr. Elizabeth Torres, a computational neuroscientist at Rutgers University and the study’s lead researcher, told FoxNews.com. “It gives us a fingerprint of that person. Then of course, as we grow and we change, 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 was inspired to study movement in relation to autism after she spent time studying the movement patterns of non-human primates. According to Torres, the movements of both primates and humans can be described by a pattern known as a Gaussian distribution. Within a few degrees of variability, this formula can predict the speed and time it takes for us to perform specific movements.
Humans move in this pattern, Torres explained, because our movement techniques are all learned from our previous experiences.
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“In a normal person, a past event informs you of a future event,” Torres said. “The past event informs you of what you’re doing now, and what you’re going to do next… Your system predicts what you’re about to do.”
But when Torres examined the movements of a child with autism as he performed martial arts, she noticed a significant difference. The child did not move in relation to this distribution pattern. In fact, his movements could not be predicted at all based on his past experiences.
“In their case, it’s like they’re living in the ‘here and now.’ The only information useful to them is what is happening to them in the moment,” Torres said. “This is a common feature of all (autistic people) – their movement distribution is non-anticipatory.”
Struck by this realization, 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.
A crucial aspect of the new method is that it records a patient’s involuntary movements – the ones 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 from their peers, but similar enough so that their unconscious movements can be measured with a newly developed set of probability distributions.
“The fact is that those distributions can be characterized with the numbers,” Jose told FoxNews.com. “With every person that we have studied, there’s a region in space (on the graph) where you can put a dot, and you would know immediately you’d have an autistic child. It gives us a quantitative way of measuring cognitive abilities by the way people move.”
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.
Treatment through self-motivation
In addition to the method’s screening success, Torres and her team demonstrated how the technique could be utilized as an early intervention therapy for autistic infants and children. The ultimate goal of the treatment: getting the children to perform certain tasks through self-motivation, rather than being told what to do. This facilitates an autistic child’s ability to learn socially acceptable behaviors on their own.
In a series of experiments, the children were connected to the motion capture system and given different computer games to play. In the first game, they had to match two geometric shapes on the computer screen by pointing at the correct shape – if they succeeded, a video they found enjoyable would play on the screen. In another game, the children had to figure out a position in the air to keep their hand, which would then prompt the video to play.
“They have to do this all by themselves, wearing sensors capturing their position,” Torres explained. “By chance, their hand might cross that region in that space. So it becomes a more systematic exploration until they discover if they put their hand in that space, they can watch the video. Then they deliberately put their hand in that space; they self-discover what they need to do.”
All 25 children who used the program were able to spontaneously discover their favorite media, and when the children would return weeks later to play the games, they remembered exactly what they needed to do in order to get the videos to play on the screen.
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.
“The system closes that feedback loop,” Torres said. “…The feedback that they need now is coming through this visual information, closing the loop using these senses, using sight and sound and touch. They’re finally getting a feedback on what they’re doing, and it helps them improve.”
An objective method for the future?
Aside from her experience studying primate movement patterns, Torres said she was also inspired to create this method due to the subjective nature of current diagnostic procedures for autism.
“The way autism is diagnosed today is through a verbal report of an observation by someone certified or trained to perform this procedure,” Torres said. “The person sits there with the child and asks a series of questions and does a series of exercises to probe imaginative thinking…. It’s all based on the observation of that person and the opinion of that person.”
Torres said current methods provide only a snapshot of the child’s behavior during the initial diagnosis. In order to improve outcomes for patients, she had hoped to create something that would enable clinicians to track children’s progress objectively and longitudinally over the course of their lives – and to provide a methodology that would offer truly personalized therapy.
Anne Donnellan, founding director of the University of San Diego Autism Institute and editor of Torres’ research, thinks this technique will revolutionize the way autism is detected and treated – although it is too early to tell whether or not the research will one day be available to the public.
“I think it is really exciting and really innovative work,” Donnellan told FoxNews.com. “I think it gives us an insight that we’ve never had – a level of objectivity that people have always strived for.”
Torres’ research was funded by the National Science Foundation and published as part of a special collection of papers in the journal Frontiers in Neuroscience.
To learn more about the screening method: The Micro-Movement Perspective
To learn more about the new treatment: Give spontaneity and self-discovery a chance in ASD: Spontaneous peripheral limb variability as a proxy to evoke centrally driven intentional acts