Evaluating changes in gait and activity associated with cognitive impairment using a home‐based technology platform

Abstract

AbstractBackgroundChanges in mobility are associated with cognitive decline in older adults. Mobility is frequently assessed in the clinic setting at episodic intervals. Passive sensors within a home‐based technology platform allow for unobtrusive collection of mobility and gait information over an extended time period. This method of high‐frequency data collection could be sensitive to early changes in mobility associated with cognitive decline.MethodWe present data for a cohort of 32 participants living alone and enrolled in the Collaborative Aging Research Using Technology (CART) Initiative aging study with a pervasive sensing and computing system deployed in their homes. Sixteen individuals with a Clinical Dementia Rating (CDR) scale score of 0.5 were matched by age, sex and education to 16 participants with a CDR of 0; 80% lived in low‐income senior apartments; 6% were non‐white. Mobility and gait data is derived from a gait line, consisting of four ceiling mounted, field‐of‐view restricted passive infrared motion sensors placed 61 cm apart in a line, in each home. The number of walking events, defined as all four sensors being triggered, was analyzed between the two groups.ResultParticipants with a CDR score of 0 had a mean age of 72.1 years and a mean MoCA score of 26.1 (range 21 – 30). Participants with a CDR score of 0.5 had a mean age of 72.2 and a mean MoCA score of 22.1 (range 15 – 27). Fifty‐six percent of participants in each group were female. Preliminary data from the gait line from a combined 1400 days for CDR 0 participants and a combined 1250 days for CDR 0.5 participants is presented here. The mean number of daily walking events detected by the gait line was significantly greater for CDR 0 participants (101.4) compared to CDR 0.5 participants (92.8, p=0.03).ConclusionAmbient sensors are able to collect longitudinal data on gait and activity levels in individuals with a technology platform deployed within their home. This unobtrusive remote mobility assessment methodology identifies individuals experiencing cognitive impairment. Further evaluation of other gait metrics and home‐based activity patterns is ongoing to explore their association with changes in cognition.