Show-Me State Times

Mild cognitive impairment (MCI) is an early indicator of Alzheimer's disease or dementia. Early identification could lead to interventions and improved outcomes, but diagnosing MCI is often long and challenging, particularly in rural areas where access to neuropsychologists is limited.

Researchers at the University of Missouri have developed a portable system to enhance the accessibility of cognitive assessments. This system combines a depth camera, a force plate, and an interface board to measure multiple aspects of motor function efficiently. The research team includes Trent Guess, Jamie Hall, and Praveen Rao from the University of Missouri.

In a recent study, the team assessed older adults, some with MCI, by having them engage in activities such as standing still, walking, and standing from a bench while counting backward in sevens. Performance data was captured by the portable system and analyzed by a machine learning model, which accurately identified 83% of individuals with MCI.

"The areas of the brain involved in cognitive impairment overlap with areas involved in motor function," Guess explained. "These can be very subtle differences in motor function related to balance and walking that our new device is able to detect but would go unnoticed through observation."

With Alzheimer's projections expected to more than double by 2060, this device could benefit millions of adults. "Alzheimer's disease is a significant problem here in the U.S.," Hall noted. "We know that if we can identify people early, we can provide early intervention to halt or slow the progression of the disease."

Hall mentioned that the team's goal is to implement the system in settings like community centers and health departments to increase screenings. "There are new drugs coming out to treat those with MCI," Hall said. "Our portable system can detect if a person walks slower or doesn’t take as big of a step because they are thinking very hard."

The team plans to continue researching with more participants to examine the system's capacity to detect fall risks and frailty in older adults. "This portable system has many other applications," Guess said, citing potential uses in sports rehabilitation and treatments for Parkinson’s disease, among others.

Guess added that the study participants are committed to the research. Hall shared, "Many of those who came in to be tested either have been diagnosed with MCI or have a family member who has Alzheimer’s disease, so they feel strongly about helping us move this forward."

The study findings were published in "Alzheimer’s Disease and Associated Disorders," with funding from the University of Missouri Coulter Biomedical Accelerator supporting the initiative.