New York, June 25 (IANS) Researchers, including one of Indian-origin, at The University of Texas have developed a durable and versatile wearable diagnostic tool that measures three diabetes-related compounds in microscopic amounts of perspiration. Also Read - The Horror! Man Gets Trapped Underground With Rats After He Falls Down a 12-Feet Sinkhole

“We believe we have created the first diagnostic wearable that can monitor these compounds for up to a week, which goes beyond the type of single use monitors that are on the market today,” said Shalini Prasad, professor of bioengineering in the Erik Jonsson School of Engineering and Computer Science. Also Read - Proud Moment! New York's Richmond Hill Stretch Co-Named 'Punjab Avenue' to Honour Community's Contribution

In a study published in Scientific Reports, Prasad and lead author Rujute Munje described their wearable diagnostic biosensor that can detect three interconnected compounds – cortisol, glucose and interleukin-6 – in perspired sweat for up to a week without loss of signal integrity. Also Read - Air Travel Latest Updates: World's Longest Flight, Singapore to New York, Set to Make Return From Next Month | Deets Inside

“We wanted to make a product more useful than something disposable after a single use,” Prasad said.

“It also has to require only your ambient sweat, not a huge amount. And it’s not enough to detect just one thing. Measuring multiple molecules in a combinatorial manner and tracking them over time allows us to tell a story about your health,” she added.

The team is alos developing an app that will receive the wearable device’s data on a cellphone.

“With the app we’re creating, you’ll simply push a button to request information from the device. If you measure levels every hour on the hour for a full week, that provides 168 hours’ worth of data on your health as it changes,” Prasad said.

That frequency of measurement could produce an unprecedented picture of how the body responds to dietary decisions, lifestyle activities and treatment.

This is published unedited from the IANS feed.