In-home walking speeds and variability trajectories associated with mild cognitive impairment

Area of Science:

• Gerontology
• Neurology
• Biomedical Engineering

Background:

• Mild cognitive impairment (MCI) is a transitional stage between normal cognition and dementia.
• Early detection of MCI is crucial for timely intervention and management.
• Objective, unobtrusive, long-term monitoring methods are needed to assess cognitive decline in real-world settings.

Purpose of the Study:

• To investigate if unobtrusive, long-term in-home assessment of walking speed and its variability can differentiate individuals with MCI from those with intact cognition.
• To explore the potential of gait parameters as early biomarkers for cognitive impairment.

Main Methods:

• Utilized passive infrared sensors in participants' homes to continuously monitor walking speed.
• Analyzed weekly mean walking speed and walking speed variability (coefficient of variation [COV]) using latent trajectory models.
• Included elderly participants from the Intelligent Systems for Assessing Aging Change (ISAAC) cohort study.

Main Results:

• Identified three distinct trajectories for mean weekly walking speed (fast, moderate, slow).
• Individuals with nonamnestic MCI (naMCI) were more likely to exhibit slower walking speeds.
• Identified four distinct trajectories for walking speed variability (COV), with naMCI participants showing patterns of highest or lowest baseline COV.

Conclusions:

• Walking speed and its daily variability show promise as early indicators of MCI development.
• Real-time gait measures may offer novel methods for detecting the transition phases leading to dementia.
• Passive in-home monitoring provides a feasible approach for long-term assessment of functional changes related to cognitive health.