Objective: To determine whether unobtrusive long-term in-home assessment of walking speed and its variability can distinguish those with mild cognitive impairment (MCI) from those with intact cognition. Methods: Walking speed was assessed using passive infrared sensors fixed in series on the ceiling of the homes of elderly individuals participating in the Intelligent Systems for Assessing Aging Change (ISAAC) cohort study. Latent trajectory models were used to analyze weekly mean speed and walking speed variability (coefficient of variation [COV]). Results: ISAAC participants living alone included 54 participants with intact cognition, 31 participants with nonamnestic MCI (naMCI), and 8 participants with amnestic MCI at baseline, with a mean follow-up of 2.6 ± 1.0 years. Trajectory models identified 3 distinct trajectories (fast, moderate, and slow) of mean weekly walking speed. Participants with naMCI were more likely to be in the slow speed group than in the fast (p = 0.01) or moderate (p = 0.04) speed groups. For COV, 4 distinct trajectories were identified: group 1, the highest baseline and increasing COV followed by a sharply declining COV; groups 2 and 3, relatively stable COV; and group 4, the lowest baseline and decreasing COV. Participants with naMCI were more likely to be members of either highest or lowest baseline COV groups (groups 1 or 4), possibly representing the trajectory of walking speed variability for early- and late-stage MCI, respectively. Conclusion: Walking speed and its daily variability may be an early marker of the development of MCI. These and other real-time measures of function may offer novel ways of detecting transition phases leading to dementia.

Potential roles of digital technologies in clinical trials

Abstract