Our research - Unobstrusive sensing in-home behaviors and health outcomes

This research contributes to the understanding of in-home behaviors associated with mild cognitive impairment (MCI) by leveraging novel digital sensing technologies. Although older adults spend approximately 83% of their day inside their residences, most existing studies focus on out-of-home mobility and its health correlates. Using digital biomarkers to measure functional outcomes holds great promise due to its potential to detect behavioral changes prior to the onset of MCI. To explore this potential, a ubiquitous sensing platform has been employed to capture spatiotemporal routines in real-world homes, tracking trips between indoor rooms over the course of a month. The findings reveal a significant association between increased bathroom usage and kitchen activities with MCI, possibly influenced by biological factors such as hormonal changes and environmental or social factors.

This novel approach demonstrates that nuanced differences in spatiotemporal routines would not be identified without continuous 24-hour data from unobtrusive sensing. The study highlights a new method for characterizing cognitive health by analyzing chronologically ordered movement across indoor locations, which may be critical for defining endpoints in clinical trials and enhancing clinical practices for chronic diseases in late life. Additionally, the research shows that older adults’ in-home movement patterns, such as the order and duration of room visits, serve as indicators of cognitive changes, with movement transition stability increasing as cognition declines. To ensure scientific rigor, reproducibility and replicability were assessed by successfully replicating previous findings using the latest generation of sensing technology and a new participant sample. This reproducibility work supports the feasibility of reducing sample sizes in Alzheimer’s clinical trials through in-home sensor monitoring.

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