Researchers at Penn State have developed a novel wearable sensor that continuously analyzes sweat in real-time. This sensor, worn on the skin like a patch, detects changes in sweat composition and provides information regarding an individual’s hydration levels, electrolyte balance, and glucose levels.
How the Sensor Works
The sensor operates by measuring electrical signals generated by sweat glands in the skin. These signals help determine the concentration of substances such as sodium, potassium, and glucose in the sweat. Furthermore, it can detect shifts in sweat pH, offering insights into a person’s overall health.
In their study published in Advanced Functional Materials, the researchers emphasized the significance of sweat as a valuable source of biomarkers, substances that indicate one’s health or disease status. Detecting these biomarkers in sweat is challenging due to their low concentrations, which can vary based on factors like exercise, diet, and environment. Past sweat sensors faced issues like low sensitivity, limited surface coverage, and instability.
To overcome these challenges, the researchers utilized laser-induced graphene (LIG) as a flexible base material for their sensor. They enhanced LIG with gold, silver alloys, and carbon-based nanocomposites, improving its conductivity and resistance. This modified LIG material measured glucose levels by sensing glucose oxidation, pH levels by detecting hydrogen ions, and temperature in sweat. These sensors were integrated into a stretchable microfluidic layer for sweat collection and analysis.
High Sensitivity and Stability for Weeks
The result is a small wearable patch, approximately the size of two postage stamps. It wirelessly sends data to a computer or mobile device for real-time monitoring. This patch offers high sensitivity and stable glucose level monitoring for up to three weeks. It surpasses previous sensors in both performance and accuracy.
In conclusion, this patch boasts high sensitivity, stability, affordability, and user-friendliness, making it a promising tool for personalized health monitoring and disease management.
