News Release

Personalized sweat sensor reliably monitors blood glucose without finger pricks

A handheld device combined with a touch sweat sensor (strip at right) measures glucose in sweat, while a personalized algorithm converts that data into a blood glucose level. Image courtesy of ACS Sensors

May 10, 2021 -- Many people with diabetes endure multiple, painful finger pricks each day to measure their blood glucose. Now, engineers at the University of California San Diego have developed a device that can measure glucose in sweat with the touch of a fingertip, and then a personalized algorithm provides an accurate estimate of blood glucose levels.

The work was published recently in ACS Sensors.

According to the American Diabetes Association, more than 34 million children and adults in the U.S. have diabetes. Although self-monitoring of blood glucose is a critical part of diabetes management, the pain and inconvenience caused by finger-stick blood sampling can keep people from testing as often as they should. And while scientists have developed ways to measure glucose in sweat, levels of the sugar are much lower than in blood, and they can vary with a person’s sweat rate and skin properties. As a result, the glucose level in sweat usually doesn’t accurately reflect the value in blood.

To obtain a more reliable estimate of blood sugar from sweat, a team led by UC San Diego nanoengineering professor Joseph Wang and Juliane Sempionatto, a nanoengineering Ph.D. student in Wang’s lab, devised a system that could collect sweat from a fingertip, measure glucose and then correct for individual variability.

The researchers made a touch-based sweat glucose sensor with a polyvinyl alcohol hydrogel on top of an electrochemical sensor, which was screen-printed onto a flexible plastic strip. When volunteers placed their fingertip on the sensor surface for one minute, the hydrogel absorbed tiny amounts of sweat. Inside the sensor, glucose in the sweat underwent an enzymatic reaction that resulted in a small electrical current that was detected by a handheld device.

The researchers also measured the volunteers’ blood sugar through a standard finger prick test, and they developed a personalized algorithm that could translate each person’s sweat glucose to their blood glucose levels. In tests, the algorithm was more than 95% accurate in predicting blood glucose levels before and after meals. To calibrate the device, a person with diabetes would need a finger prick only once or twice per month. But before the sweat diagnostic can be used to manage diabetes, a large-scale study must be conducted, the researchers say.

The work was supported by the UC San Diego Center for Wearable Sensors and the National Research Foundation of Korea.

Paper title: “Touch-Based Fingertip Blood-Free Reliable Glucose Monitoring: Personalized Data Processing for Predicting Blood Glucose Concentrations.”

Media Contacts

Liezel Labios
Jacobs School of Engineering