Researchers Develop New AI Tool for Timely Alzheimer's Detection

These AI-powered motor function assessments provide an affordable and effective method for the early detection of mild cognitive impairment (MCI), a condition often seen as a precursor to dementia.

Researchers at the University of Missouri have developed a portable system to detect early cognitive decline. Reportedly, this low-cost portable device identifies motor function changes associated with cognitive decline.

These AI-powered motor function assessments provide an affordable and effective method for the early detection of mild cognitive impairment (MCI), a condition often seen as a precursor to dementia.

“The areas of the brain involved in cognitive impairment overlap with those controlling motor function, so when one is diminished, the other is impacted as well,” explained Trent Guess, an associate professor involved in the study. “Our device can detect very subtle changes in balance and walking that would otherwise go unnoticed”, he further stated.

A Portable Solution for Cognitive Decline Detection

Diagnosing MCI has traditionally posed challenges, especially in rural areas with limited access to specialists. To address this, researchers at the University of Missouri designed a cost-effective, portable system capable of detecting subtle motor function differences that may indicate cognitive decline.

The device consists of a depth camera, a force plate, and an interface board to capture detailed movement data. Participants, including older adults with MCI, were asked to complete tasks like standing, walking, and transitioning from sitting to standing. For added complexity, they performed these activities while counting backward in intervals of seven.

The data collected was analyzed using machine learning, a subset of AI, achieving an impressive 83% accuracy in identifying MCI. Among various AI models tested, decision trees delivered the most reliable results, boasting a sensitivity of 0.83 and a perfect specificity of 1.00.

Urgent Need for Early Diagnosis

Alzheimer's disease affects millions globally, with US cases alone projected to more than double by 2060, according to the Centers for Disease Control and Prevention. Despite this prevalence, only 8% of individuals with MCI are formally diagnosed, delaying interventions and reducing the effectiveness of treatments.

Current diagnostic techniques, such as PET scans and cerebrospinal fluid tests, are costly and require specialized facilities, making them inaccessible for large-scale use. AI-powered motor function systems bridge this gap by offering a scalable and cost-effective alternative.

AI applications extend beyond motor function assessments to home-based cognitive and speech analysis. For instance, the TAS Test, developed in Australia, evaluates motor skills, speech, and cognitive function through an AI-driven online platform. Requiring only a keyboard and webcam, the tool has demonstrated effectiveness in identifying early Alzheimer’s symptoms.

By integrating data from various sources—motor function, speech patterns, and cognitive tests—AI enhances diagnostic accuracy and enables the development of robust predictive models. Multimodal AI screening provides a practical and scalable solution for early diagnosis.

Expanding the Reach of AI-Powered Detection

The University of Missouri researchers aim to implement their motor function system in public health settings such as senior centers, rehabilitation clinics, and assisted living facilities. This technology may also assist in diagnosing conditions beyond dementia, such as frailty, fall risks, concussions, and neurodegenerative diseases like Parkinson’s.

“There are new drugs coming out to treat those with MCI, but you need a diagnosis to qualify for the medications,” Hall said. “Our system can detect if a person walks slower, takes smaller steps, or shows balance issues. These are subtle signs of cognitive strain that might otherwise go unnoticed.”

Future research will focus on refining the system and broadening its applications to other medical and rehabilitative fields.

“This technology can be beneficial in many ways, from sports rehabilitation to knee and hip replacements,” Guess said. “Movement is fundamental to who we are, and our goal is to create tools that improve people’s quality of life.”

“Many of those who volunteered for our study have loved ones with Alzheimer’s and want to help push this research forward,” Hall said. “It highlights why this work is so important.”

Stay tuned for more such updates on Digital Health News.