Scientists from University of California – Berkeley are developing wearable skin sensors able to detect the sweat rate, and electrolytes and metabolites in sweat. In an article published in Science Advances, the team describe a sensor design that can be rapidly manufactured using a 'roll-to-roll' processing technique which prints the sensors onto a sheet of plastic like words on a newspaper.
"The goal of the project is not just to make the sensors but start to do many subject studies and see what sweat tells us -- I always say 'decoding' sweat composition," said Ali Javey, a professor of electrical engineering and computer science at UC Berkeley. “For that we need sensors that are reliable, reproducible, and that we can fabricate to scale so that we can put multiple sensors in different spots of the body and put them on many subjects.”
The sensors contain a spiralling microscopic tube, or microfluidic, that wicks sweat from the skin. By tracking how fast the sweat moves through the tube, the sensors can determine how much a person is sweating. The tubes are also outfitted with chemical sensors that can detect concentrations of electrolytes like potassium and sodium, and metabolites like glucose.
“Traditionally what people have done is they would collect sweat from the body for a certain amount of time and then analyse it,” said Hnin Yin Yin Nyein, a graduate student in materials science and engineering at UC Berkeley. “Using these wearable devices we can now continuously collect data from different parts of the body, for example to understand how the local sweat loss can estimate whole-body fluid loss.”
Researchers hope that one day, this technology could eliminate the need for more invasive procedures and provide real-time updates on health problems.
“There's been a lot of hope that non-invasive sweat tests could replace blood-based measurements for diagnosing and monitoring diabetes, but we've shown that there isn't a simple, universal correlation between sweat and blood glucose levels,” said Mallika Bariya, a graduate student in materials science and engineering at UC Berkeley. “This is important for the community to know, so that going forward we focus on investigating individualised or multi-parameter correlations.”
