This Project Grant award from the National Institute on Aging (CFDA 93.866 - Aging Research) to Tufts University supports the development of a multi-modal biosensing and predictive analytics system for continuous monitoring of mobility and cognition in an aging population. The $269,316 award aims to create a wearable sensor system and advanced machine learning algorithms to enable early detection and prediction of Alzheimer's disease and related dementias.
Specifically, the project will develop a flexible, breathable, and inconspicuous sensor patch that can provide real-time monitoring of biophysical domains such as gait, posture, heart rate, and location. Building on this sensor platform, the researchers will develop statistical machine learning models to estimate and track cognitive function and mobility over time. The system will be validated through a feasibility study with 20 older adults, starting in a controlled lab setting and extending into real-world scenarios. The goal is to advance personalized sensing and health informatics to support early detection and monitoring of age-related cognitive and mobility declines.