Monday, December 10, 2012
The best communicator at UT Arlington can't be found in a lecture hall or on a theater stage. He won't wow you with his stature (being only two feet tall) or impress with his sonorous voice (it's rather monotone). But what he can do—what he was literally built for—may make it easier for doctors to diagnose and treat autism. His name is Zeno, and he's the impressive bundle of wires, Frubber, and sensors at the center of Electrical Engineering Associate Professor Dan Popa's work on autism.
Characterized by difficulties in social interaction, communication, and repetitive behaviors, autism is a complex disorder of brain development. According to the U.S. Centers for Disease Control and Prevention, about one in 88 American children are on the autism spectrum, with boys about five times more likely to be diagnosed than girls. Traditional detection methods for the disorder rely on speech and social interactions, which require that the child be old enough to talk. Were there a way for doctors to focus on their patients' motions instead, they might be able to detect the condition earlier, and thus begin treatment earlier.
"Recent studies have shown that robots can be helpful to children with autism," explains Dr. Popa, who directs the Next Generation Systems group at the UT Arlington Research Institute. "It turns out that the kids are attracted to robots. In fact, they'd probably rather interact with them than with humans."
So, he and his research partners—Hanson RoboKind, the Dallas Autism Treatment Center, the University of North Texas Health Science Center (UNTHSC), and Texas Instruments—teamed with Hanson Robotics to create a lifelike robot for their use. Created by Hanson Robotics owner and former Disney Imagineer David Hanson, it stands about two feet tall and has an artificial skin made of Frubber, a flexible material that can mold into different shapes. Hanson RoboKind was responsible for Zeno's design—the name comes from Hanson's son—with UT Arlington mechanical engineering alumnus Richard Margolin serving as chief engineer for the project.
After Hanson provided the initial robot, the research team embedded a more performance-controlled system into it. This gives it the ability to not only interact with the children, but also to measure their movements and indicate what therapies might work best for them. Popa and his engineers currently employ "off-the-shelf" equipment for Zeno's controls, but he eventually wants to create custom controllers using chips from Texas Instruments (National Instruments also has given his team equipment to test).
These controls combined with the robot's innovative Frubber skin allow Zeno to accurately mimic human movement and facial expressions like smiling, to maintain eye contact with a person, and to follow movements with his head and eyes. This human-like appearance sets Zeno apart from robots used in about a dozen similar studies being conducted worldwide, and, researchers believe, is key to his ability to detect autism symptoms.
It's a belief that flies in the face of a commonly accepted hypothesis, the uncanny valley. Proposed in 1970 by Japanese researcher Masahiro Mori, the theory posits that when human observers are presented with robots that look and act almost, but not exactly, like actual human beings, they feel uneasy. The team's success with Zeno is challenging that long-held idea.
In fact, the researchers want the robot to look and act as human-like as possible. They feel that if children are to learn movements by mimicking Zeno, then the robot's movements need to be as fluid and lifelike as possible. Otherwise, Popa says, the kids will move awkwardly—like a robot.
When working with children, the researchers use Zeno in three distinct ways. In "scripted" mode, the robot does default motions like waving, and the child is encouraged to follow the movement. In "therapist" mode, the therapist performs a motion that the robot plays back, using controls created by Popa's team. This allows him or her to tailor a session to a particular child's needs. Finally, in "direct" mode, the robot uses technology found in an Xbox Kinect to detect human motion and react, much like when a baby plays in front of a mirror.
According to Nahum Torres, a Ph.D. student in UT Arlington's Electrical Engineering Department, the researchers try to teach the children simple movements, then, once those are learned, add speech and facial expressions.
"When we say hello to someone, we might wave, then say hello, then smile," he says. "Children with autism have trouble processing two commands at a time, so the robot helps them learn to complete a set of tasks."
For Nicoleta Bugnariu, associate professor at UNTHSC and a physical therapist/neuroscientist, motor control issues are what she is most interested in learning from the children's interactions with the robot.
"How these children keep their balance, reach for an object, and move about a room may be extremely important in diagnosing autism," Dr. Bugnariu says. She feels that if we can detect these motor biomarkers and determine the timing of these differences during the developmental process, it would greatly benefit diagnosis and treatment.
"In the first two years of life, language is a small part of a person," Bugnariu continues. "Children move first, then speech comes. We can't wait until they use speech. We need to determine sooner who has autism."
One of the children the researchers have observed is Pamela Rainville's 7-year-old son, Anthony. Rainville found out about the research project from Carolyn Garver, director of the Dallas Autism Treatment Center, and thought it might benefit Anthony.
"It's always good for Anthony to be put in different situations, things outside his normal routine," she says. "Anytime he can be around other people, it's a good learning and growing experience for him."
Anthony has worked twice with Zeno so far. Rainville believes her son got more out of the second meeting than the first, and she expects he'll get even more out of subsequent interactions with the robot.
"This second time, Anthony fist-bumped Zeno, which was great," she says. "He was a little more relaxed."
Popa and his team routinely visit UNTHSC to analyze the data collected through the experiments with the robot, and then use that information to evaluate the quality of the interaction.
"It gives us tons of data we can study to determine whether there is a correlation between a child's improvement and their work with the robot. I think there is, but it's too early to tell," he says.
One big reason why it's too early is that the pool of children Popa and the researchers at UNTHSC have been able to work with is very small. They have only had sessions with about five kids and need far more to determine trends.
To recruit more subjects, Popa has teamed with Marc Schwartz, director of UT Arlington's Southwest Center for Mind, Brain, and Education, to create a room aimed at autistic children at the Fort Worth Museum of Science and History. Dr. Schwartz's goal is to provide the kids with an experience that will allow them to benefit from the museum, and he believes that including a robot could help. For his part, Popa hopes that it will allow his team to collect more data to add to their research.
"We also want to take the robot out of the lab as much as possible and see if it has other uses," Popa says. "For instance, robots like Zeno could be used in occupational or physical therapy to help people relearn motions."
As of now, there are really no biological methods of determining autism.
"We just observe," says Dr. Garver. "That's why this research is so important. If we can document that a certain eye gaze or motor movement means some level of autism, this could help in developing ways to treat it early on."
Parents like Pamela Rainville who are working with Popa and his team understand this. They know that whatever data the engineers and doctors discover may be more beneficial for future generations of autism patients than their own children. But that's OK.
"I know it might not help Anthony," Rainville says. "But I think if this research can help other children with autism through early diagnosis, then that's well worth the visits."
Sat, Dec 7 – All Day
FIRST LEGO League
Sat, Dec 7 – All Day
Sun, Dec 8 – All Day
Mon, Dec 9 – All Day
CSE Colloquium: Nicholas Hopper
Mon, Dec 9 – 11:30 am
Tue, Dec 10 – All Day
Wed, Dec 11 – All Day
Thu, Dec 12 – All Day