3D-Printed, Adhesive-Free Wearable to Transform Health Monitoring

Conventional wearable health devices rely on sensors that stick directly to the skin, but the skin constantly renews itself. This natural shedding of skin weakens adhesives and clogs the sensors, meaning wearables that use adhesives need to be reapplied every few days. As a result, the ability to collect reliable data over extended periods is restricted. Now, a new study published in Nature Communications introduces a novel, adhesive-free, 3D-printed wearable that offers a more durable solution for monitoring a user's physiological state continuously.

Developed by researchers at the University of Arizona College of Engineering (Tucson, AZ, USA), the device measures water vapor and gases emitted from the skin, providing real-time data about a user’s hydration, metabolic changes, and stress levels. Designed to be worn on the forearm, the 3D-printed cuff-like device is capable of continuous use. Its sensors continuously measure gas emissions from the skin, comparing them with the normal concentration of gases in the air. Unlike traditional adhesive-based wearables, which only capture intermittent data, this device provides continuous, real-time feedback that can be monitored via a smartphone or computer through a secure Bluetooth connection.

With this device, athletes can track hydration and exertion levels throughout their training sessions. It can also be used to monitor mental health conditions and chronic diseases, aiding in prevention and treatment. Additionally, monitoring stress-related physiological markers in the gases emitted by the skin could help identify early signs of metabolic imbalances. Moving forward, the research team plans to expand the range of biomarkers detected and integrate sophisticated data analytics to provide more personalized health insights over longer periods.

"This opens an entirely new space of biomarkers," said Philipp Gutruf, an associate professor of biomedical engineering and member of the BIO5 Institute at the U of A who co-authored the study. "For example, you can capture the metabolic signatures of exercise or stress without interrupting the subject's normal routine. Previously, measurements of this kind required an entire room of equipment."