Using wrist-worn devices and room-level positioning infrastructure to capture spatial routines, social synchrony, and longitudinal activity trends in natural home settings.
One participant · 10 days (Feb 8–17, 2026) · X-axis: 12:00 noon → 12:00 (+1 day) · Hover for details
Understanding how people actually use their living spaces — and how those patterns shift over time or in response to interventions — is nearly impossible to study in a laboratory. Self-report diaries are unreliable; direct observation is intrusive and impractical at scale.
This case study demonstrates how Care Active's indoor sensing infrastructure enables continuous, passive behavioral monitoring across multi-room environments with no researcher presence required.
Participants wear the Care Watch, a lightweight wrist-worn device that communicates with small Bluetooth Stations installed in each room of the home. Signal strength triangulation provides room-level location estimates continuously throughout the day.
Care Watch requires no charging — its battery lasts over 6 months under continuous use, eliminating a significant compliance burden in long-duration studies. Participants simply wear it; researchers never need to schedule device collection for recharging.
Combined with the watch's built-in accelerometer, the system produces a longitudinal record of both where participants spend time and how active they are in each space — without cameras or microphones.
Social Synchrony Analysis. In household studies, overlapping presence data from multiple participants reveals co-location patterns — a proxy for social interaction and relationship dynamics that is otherwise difficult to measure continuously.
Longitudinal Activity Trends. Tracking room-specific activity levels over months enables researchers to detect gradual behavioral change — relevant to aging research, rehabilitation outcomes, and mental health studies.
Spatial Routine Disruption. Deviations from established spatial patterns (e.g., spending significantly less time in the kitchen, or increased nighttime movement) can serve as sensitive behavioral markers in clinical research.
Explore how we capture outdoor mobility without exposing participant location data.
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