George Mason University psychology professor Yi-Ching Lee is conducting research to learn how driving can be used to monitor health conditions.
As a part of the study “Diagnostic Driving: Real-Time Driver Condition Detection Through Analysis of Driver Behavior,” Lee and her team are looking at how teens and young adults with Attention Deficit Hyperactivity Disorder (ADHD) operate cars when they take their ADHD medication versus when they forget a dose, or if the medication dosage needs to be adjusted.
“We want to know how the driving behaviors are different under well-controlled medication and out-of-control medication,” she says.
Machine-learning techniques are used to pick up patterns in driving behaviors, especially unsafe maneuvers, and to detect nearby traffic, road configurations, and other data.
More than 300 participants will be a part of the four-year study through the use of driving simulators or by driving their own cars outfitted with special sensors and cameras.
“If successful, our work will lead to transformative changes in how we monitor many types of patients, not only those with ADHD, but those with other medical and post-surgical conditions,” Lee says.
Perhaps in the future, machine learning-equipped computers in cars can monitor behaviors. If deviations are detected, then warnings can be generated and feedback sent to care providers.
The study, which also includes researchers from Drexel University, the Children’s Hospital of Philadelphia, and the University of Central Florida, is funded by an $891,135 grant from the National Science Foundation.