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Detecting the Impact of Older Adult Healthy Brain Aging Behaviour Adoption Using Smart Home Technology
Katherine Wuestney1, Regan Jenkins1, Brooke F Beech1
1Washington State University, Pullman, WA, USA.
Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science
|January 12, 2026
Summary
Smart homes effectively monitor behavior changes in older adults undergoing healthy brain programs. This technology quantifies progress, supporting cognitive health and aiding sustainable behavior adoption for aging well.
Area of Science:
- Gerontology
- Health Informatics
- Behavioral Science
Background:
- Cognitive decline is a concern for older adults.
- Traditional methods for assessing behavior change are error-prone.
- Healthy brain behaviors can sustain cognitive health.
Purpose of the Study:
- To introduce and apply a smart home-based method for monitoring and quantifying behavior change.
- To analyze behavior changes in older adults participating in a healthy brain program.
- To assess the effectiveness of smart home technology in supporting behavior change goals.
Main Methods:
- Utilized CASAS Smart Home in a Box (CASAS ShiB) in 14 participants' homes.
- Collected continuous data at baseline and during a six-week program.
- Applied the Behaviour Change Detection (BCD) algorithm to quantify weekly behavior changes.
- Employed a virtual classifier to analyze change types and compare with self-reported adherence.
Main Results:
- Behavior change increased by 23.22% from baseline by the program's end.
- Smart home data provided objective quantification of behavior modification.
- The virtual classifier analyzed observed changes against self-reported adherence.
Conclusions:
- Smart home technology offers a reliable method for monitoring behavior change in older adults.
- Data mining techniques combined with smart homes can support adherence to healthy brain aging behaviors.
- This approach enhances the assessment of interventions aimed at cognitive health in aging populations.
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