Assessing the Feasibility of Multi-modal Biosensing for Monitoring Mobility and Cognition in Older Adults

Devices capable of measuring, interpreting, and providing guidance based on a range of biosignals have significantly broadened the access to health information. Nevertheless, the majority of these platforms are designed for a demographic already proficient in technology, thereby excluding older adults, a group facing unique health challenges and often experiencing technological apprehension. To address this disparity, this study aims to demonstrate the feasibility of employing a wearable eutectogel-sensor patch system to monitor and analyze posture, movement, heart rate, and respiration of older adults within their natural living environments. Furthermore, investigators seek to develop algorithms that correlate these real-time data streams with physical and cognitive performance outcomes. Concurrently, they will investigate the feasibility of employing hydrogel microneedle patches for the passive collection of interstitial fluid (ISF) to measure key biomarkers associated with stress and inflammation, specifically cortisol, dopamine, and C-reactive protein (CRP). These biomarkers serve as critical indicators of physiological stress, mood regulation, and systemic inflammation, which are closely associated with cognitive decline, frailty, and diminished quality of life in the aging population. Eutectogel sensor patches are flexible, breathable, inconspicuous, and designed for long-term wear. They can be positioned strategically to provide direct, continuous, real-time monitoring of posture, motion, heart rate, and respiration. We now propose to determine the feasibility of using a eutectogel sensor patch system to continuously collect posture, motion, heart rate, and respiration data in free-living older adults. Investigators will secondly assess the feasibility of measuring dopamine, cortisol, and CRP from ISF collected with a microneedle patch and correlate them with the same analytes measured in saliva. These analytes were selected due to their relevance in detecting chronic stress and systemic inflammation-conditions that are highly prevalent and often underdiagnosed in the aging population. The research objectives are significant because they aim to bridge the technological and demographic gap through a combined sensing system that enables seamless and meaningful health monitoring in real-world settings.