Dr. Matthew Goodwin, Northeastern University – Autism Studies and Wearable Technology
In today’s Academic Minute, Dr. Matthew Goodwin of Northeastern University reveals how wearable technology is improving the quality of autism studies.
Matthew Goodwin is an assistant professor of health informatics at Northeastern University in Boston, Massachusetts. His current research project seeks to improve the understanding of minimally verbal children with autism spectrum disorder. He holds a Ph.D. from the University of Rhode Island.
Dr. Matthew Goodwin – Autism Studies and Wearable Technology
One in 88 children is diagnosed with an autism spectrum disorder. It is more common than childhood cancer, AIDS, diabetes, and spina bifida combined. This creates a public health problem: There will always be more people with ASD than experts to assess and teachers to assist them.
Yet much of today’s research doesn’t have a direct impact on the people who are living with ASD or their caregivers. It’s primarily focused on what causes the disorder, and we’re a long way from understanding that.
Most current research focuses on a convenience sample of high-functioning children with the mildest form of ASD; children who have normal IQs and good verbal ability. This sample is “convenient” because they can go to a lab with an unfamiliar person for some undefined period of time and perform tasks they’ve never done before—all of which requires a lot of self-regulation.
But at as many as half of children on the autism spectrum are too severely impacted to comply with current research protocols. These are the children we understand the least and the ones we need to help the most.
So we’re taking the lab to them. I work with computer scientists and electrical engineers to make that happen—experts who create sensors that can be woven into clothes, embedded into accessories, or inserted into devices that can be carried or worn. The devices continuously record physical activity patterns and autonomic nervous system sensing—that is, how a body is responding biologically.
To interpret the data, we also need context: where the person is and what he or she is doing. So we also “instrument spaces” with video cameras, microphones, and radio-frequency identification tags.
By bringing these wearable and environmental technologies together, we get powerful information in natural settings—at home, at school, and in the community—about what is happening to an individual with more challenging forms of ASD. This helps us understand them better and identify more impactful treatments.