Sweat Sensor for Blood Glucose Monitoring without Finger Pricks
A handheld device combined with a touch sweat sensor measures glucose in sweat, while a personalized algorithm converts that data into a blood glucose level.
Many people with diabetes endure multiple, painful finger pricks each day to measure their blood glucose. Researchers at the University of California San Diego have developed a device that can measure blood glucose in sweat with the touch of a fingertip, and then a personalized algorithm converts those readings into accurate blood sugar estimates.
As glucose levels in sweat can vary from person to person, the sensor incorporates algorithms that personalize the measurement for each user, requiring finger-prick calibration once or twice each month.
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 need for regular finger pricks is a barrier for many patients with diabetes in regularly testing their glucose levels, as the procedure is painful, inconvenient, and for many patients it has to be done many times every day.
Poor control of glucose levels leads to a host of serious health issues in the long term, so ensuring that patients can test and adjust their glucose levels often is crucial for the health of this patient population.
Sweat Glucose Testing
Diabetes prevalence has been rising exponentially, increasing the need for reliable noninvasive approaches for glucose monitoring. This issue has inspired new forms of testing technology that are minimally invasive and avoid or reduce the number of required finger pricks.
Different biofluids have been explored recently for replacing current blood finger-stick glucose strips with noninvasive painless sensing devices. One such promising approach involves sweat testing.
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 sweat is released in small amounts near continuously under normal conditions and contains glucose concentrations that are reflective of blood glucose levels, it represents a promising testing method.
Although glucose levels in sweat correlate loosely with blood glucose levels, there are significant levels of variability from person to person. The levels of glucose in sweat tend to be much lower than that in the blood, and rates of sweating can also affect the measurements.
Consequently, a ‘one size fits all’ approach to sweat glucose testing clearly isn’t as accurate as it could be. To address this, these researchers have developed a device that can provide a personalized measurement for each patient. A user simply places their finger on the sensor for a period of 1 minute to collect enough sweat to test.
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.
The new painless and simple glucose self testing protocol leverages the fast sweat rate on the fingertip for rapid assays of natural perspiration, without any sweat stimulation, along with the personalized sweat response to blood concentration translation.
Primary Reference:
- Touch-Based Fingertip Blood-Free Reliable Glucose Monitoring: Personalized Data Processing for Predicting Blood Glucose Concentrations. Juliane R. Sempionatto, Jong-Min Moon, Joseph Wang. ACS Sens. , April 19, 2021. American Chemical Society
- UC San Diego Center for Wearable Sensors