Portable system detects mild cognitive impairment in older adults

Mild cognitive disorders (MCI) can be an early indicator for Alzheimer’s disease or dementia, so identifying that with cognitive issues can lead to interventions and better results early. But diagnosing MCI can be a long and difficult process, especially in rural areas where access to recognized neuropsychologists is limited.

To increase accessibility for cognitive reviews, a team of researchers from the University of Missouri created a portable system to efficiently measure multiple aspects of the engine function. The device is simple and affordable and combines a depth camera, a power plate and an interface board.

The interdisciplinary team of Mizzou researchers includes Trent Guess, a associate professor at the College of Health Sciences, Jamie Hall, professor of the Associate Education at the College of Health Sciences, and Praveen Rao, a associate professor at the College of Engineering. In a recent study, the team investigated older adults, some of whom had MCI, and asked them to complete three activities: standing still, walking and error of a bank. The catch? Participants had to complete these activities and at the same time count back in intervals of seven.

Based on their performance, which were recorded by the new portable system, the data was entered in a machine learning model – a kind of artificial intelligence – that 83% of those in the study with MCI accurately identified.

The areas of the brain involved in cognitive impairment overlap each other with areas of the brain involved in the motor function, so when one is reduced, the other is also influenced. This can be very subtle differences in engine function related to balance and run that our new device can detect but would go unnoticed by observation. “

Trent Guess, Association Head Lecturer, College of Health Sciences, University of Missouri

With the number of Americans with Alzheimer’s disease, which is expected to more than doubles by 2060 according to the Centers for Disease Control and Prevention, the portable device can help millions of older adults, since MCI is one of the precursors of Alzheimer and Dementia.

“Alzheimer’s disease is here in the US an important problem that we know that if we can identify people early, we can offer early intervention to stop or delay the progression of the disease,” Hall said. “Only about 8% of people in the US who are assumed to get MCI will receive a clinical diagnosis.”

Hall added that the long -term objective of the team gets the new portable system in various environments, such as health departments from the province, assisted living facilities, community centers, physiotherapy clinics and senior centers to make more screening possible.

“New medicines come out to treat people with MCI, but you need a diagnosis of MCI to be eligible for the medicines,” Hall said. “Our portable system can detect whether a person is running slower or is not going so big because they think very hard. Some people have more waving and are less balanced or are slower to get up when they sit. Our technology can measure these subtle differences in a way that you couldn’t do with a stopwatch.”

Guess will continue the research with extra participants and also look at the ability of the portable system to detect the risk of falling and vulnerability in older adults.

“This portable system also has many other applications, including looking at people with concussion, sports rehabilitation, ALS and Parkinson’s disease, knee replacements and hip replacements,” Guess said. “Moving is an important part of who we are. It is worth seeing that this portable system can be useful in many different ways.”

And those who participate in the investigation are invested in the investigation, Hall added.

“Many of those who came in to be tested have been diagnosed with MCI or have a family member who has Alzheimer’s disease, so they find us strong to help us help,” Hall said. “It really strengthens why this is so important to me.”

“Feasibility of using a new, multimodal motor function assessment platform with machine learning to identify people with mild cognitive disorders” was published in Alzheimer’s disease and associated disorders. Financing was provided by the Biomedical Accelerator of the University of Missouri Coulter, who offers internal financing for engineers and clinicians who are interested in cooperation to develop devices that improve society.