Feasibility of Wearable Sensors for Older Adults
This observational study is exploring how well wearable sensors, specifically Eutectogel Sensors and Microneedle Patches, can monitor older adults. These devices will track things like posture, heart rate, and breathing, and collect body fluids to measure stress and inflammation markers (like cortisol, dopamine, and C-reactive protein). The goal is to see if this combination of data can create an easy-to-use system for personalized health monitoring at home. You might be able to join if you are 65 or older, can use a smartphone, and are willing to participate. The study aims to understand if these devices can successfully gather important health information over an 8-day period. The current recruitment status is unclear.
- Study design
- This is an observational study planning to enroll 20 participants. It is not specified if it is randomized or blinded.
- What's involved
- Not specified in the trial record.
- Compensation
- Not stated in the trial record.
- Follow-up
- Participants will be monitored from enrollment to the end of the study period at 8 days.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
Assessing the Feasibility of Multi-modal Biosensing for Monitoring Mobility and Cognition in Older Adults
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- Sameer Sonkusale, PhD · PRINCIPAL_INVESTIGATOR · Tufts University
Who to contact
Opens a ready-to-send draft in your own email app — review before sending.
What this trial measures
- Subtle biomechanical signals and interstitial fluid with key biomarkers.From enrollment to end of study period at 8 days.
We propose the use of eutectogel-based strain sensors as a soft, conformable platform for capturing subtle biomechanical signals, including posture shifts, respiratory motion, and joint movements. These gels offer unique advantages in comfort and stretchability that make them ideal for long-term use by older adults. Complementing this, we integrate hydrogel-based microneedle patches for the continuous and minimally invasive collection of interstitial fluid to measure key biomarkers: cortisol and dopamine (using the PAA/GelMA microneedle-dPAD system) and C-reactive protein (via the Gelatin/OxP microneedle µPAD platform). These biomarkers are critically relevant to monitoring stress, inflammation, and mental health-all major contributors to declining independence in aging populations. By applying machine learning methods to passively interpret this multimodal dataset, our approach addresses the unmet need for integrated, unobtrusive health monitoring systems tailored to the aging popula