Passive-ambient smart home sensors offer a unique, privacy-preserving opportunity to continuously monitor health and functional independence in senior living. By analyzing subtle patterns in daily life (e.g., appliance use, room transitions, door movements), we can derive digital biomarkers to act as leading indicators for cognitive, metabolic, or physical health decline.
- As part of our research team, you will dive into ambient sensing, analyze real-world in-home datasets, and help develop cutting-edge behavioral health scoring models.
- You will perform a comprehensive literature review on ambient sension for health applications.
- Furthermore, you will preprocess and analyze passive sensor data (activity, presence, power usage) collected from our multi-home study cohort.
- You will research, establish, and validate mathematical scoring algorithms that condense meaningful insights from the data.
- Additionally, you will investigate secondary behavioral biomarkers, exploring concepts like nutrition/appliance tracking and sleep/mobility patterns.
- Moreover, you will validate and showcase your algorithms in controlled environments, including inside a health-centric tiny home.
- Finally, you will document research findings, code, and evaluate results for internal presentations and potential scientific publication.