Overview
Mild cognitive impairment (MCI) is often an early sign of Alzheimer’s disease or dementia. Early detection can lead to timely interventions and improved outcomes. However, diagnosing MCI can be challenging, particularly in rural areas where access to neuropsychologists is limited.
Research Development
A team from the University of Missouri has developed a portable system designed to assess various aspects of motor function efficiently. This device is both simple and affordable, utilizing:
- Depth camera
- Force plate
- Interface board
Study Details
The interdisciplinary research team, including experts from the College of Health Sciences and the College of Engineering, conducted a study involving older adults, some diagnosed with MCI. Participants performed three tasks:
- Standing still
- Walking
- Standing up from a bench
While completing these tasks, participants also counted backwards by sevens, which added a cognitive challenge. The system recorded their performance, and the data was analyzed using a machine learning model, successfully identifying 83% of participants with MCI.
Significance of Findings
According to Trent Guess, one of the researchers, the brain areas responsible for cognitive impairment overlap with those involved in motor function. Subtle differences in motor skills related to balance and walking can indicate cognitive issues that might otherwise go unnoticed.
Future Implications
With projections from the CDC indicating that the number of Americans with Alzheimer’s could more than double by 2060, this portable device could significantly aid in early detection and intervention for millions of older adults.
Jamie Hall, another researcher, emphasized the importance of early diagnosis, noting that only about 8% of individuals believed to have MCI receive a clinical diagnosis. The team aims to implement this system in various settings, including:
- County health departments
- Assisted living facilities
- Community centers
- Physical therapy clinics
- Senior centers
Broader Applications
The researchers plan to explore the system’s potential for detecting fall risks and frailty in older adults. Additionally, the device could be beneficial for:
- Concussion assessments
- Sports rehabilitation
- Conditions like ALS and Parkinson’s disease
- Knee and hip replacements
Community Engagement
Participants in the study often have personal connections to MCI or Alzheimer’s, which drives their commitment to advancing this research.
Conclusion
The study titled “Feasibility of Using a Novel, Multimodal Motor Function Assessment Platform With Machine Learning to Identify Individuals With Mild Cognitive Impairment” was published in Alzheimer’s Disease and Associated Disorders. The research was supported by the University of Missouri Coulter Biomedical Accelerator.