REAL-TIME location data revealed rest-activity rhythm phenotypes in advanced dementia well tracking sleep disruption and agitation.
Rest-Activity Rhythms Captured with RTLS Wearables
Disrupted sleep and circadian rhythms are common in dementia and can affect safety, quality of life, and caregiver burden. In a new study, researchers evaluated whether a wrist-worn real-time location system (RTLS) could move beyond its typical role in nurse call and elopement prevention to quantify rest-activity rhythms in people with advanced dementia living in residential care.
The team continuously tracked participants’ location for up to 16 weeks in a specialized dementia unit. In 47 residents (21 women; mean age 80.1 years), distance moved in 15-minute windows was converted into digital markers describing both the intensity and rhythmicity of movement patterns, using parametric and non-parametric features. Researchers then applied panel and mixed effects models to examine how these markers related to repeated clinical assessments over time.
Six Rest-Activity Phenotypes Linked to Symptoms
Higher activity intensity correlated with increased clinical motor agitation scores. Markers reflecting disrupted rhythmicity and reduced nighttime time in bed were associated with difficulty falling asleep and increased nighttime motor agitation, suggesting that objective rest-activity rhythms may mirror clinically meaningful sleep disruption.
Using unsupervised machine learning, the investigators identified six distinct rest-activity phenotypes across one-week periods: high time in bed, well-regulated, low stability, severe rhythm disturbance, nighttime active, and a highly active individual. These phenotypes differed by age, cognition, mood disturbance, and functional status, highlighting heterogeneity in rest-activity rhythms even within an advanced dementia population.
Toward Data-Driven Dementia Care
Across analyses, increased activity intensity, decreased rhythmicity, and less time in bed at night were consistently associated with higher motor agitation and sleep disruption. The findings suggest that RTLS-derived rest-activity rhythms could provide scalable digital markers for monitoring behavioral and psychological symptoms of dementia in residential settings, supporting more data-driven, evidence-based dementia care.
Reference: Karam Y et al. Digital markers and phenotypes of rest-activity rhythms in people with advanced dementia using real-time location data. J Gerontol A Biol Sci Med Sci. 2026; DOI:10.1093/gerona/glaf288.
