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This New Wearable Device Can Perform Sweat Analysis For Disease

sweat analysis
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Researchers have developed a wearable device that can do sweat analysis to help diagnose cystic fibrosis, diabetes and other diseases.

The sensor collects sweat, measures its molecular constituents and then electronically transmits the results for analysis and diagnostics through a smartphone.

Sweat analysis could completely change the way we diagnose and monitor health, optimize performance, and save billions in healthcare costs.

The wearable device developed by researchers from the Stanford University and the University of California, Berkeley consists of five sensors that track, through sweat, levels of glucose, lactate, sodium and potassium.

 Unlike previous sweat collectors, the new device does not require patients to sit still for a long time while it collects sweat from them.

The wearable device is a two-part system of flexible sensors and microprocessors that sticks to the skin, stimulates the sweat glands and then detects the presence of different molecules and ions based on their electrical signals.

High chloride ion levels, for example, are an indicator of cystic fibrosis while high blood glucose levels can indicate diabetes.

Cystic fibrosis is a genetic disease that causes mucus to build up in the lungs, pancreas and other organs.

Conventional methods for diagnosing cystic fibrosis require that patients visit a specialized center and sit for 30 minutes while electrodes stimulate sweat glands in their skin to provide sweat for the test.

However, the wearable sweat sensor stimulates the skin to produce minute amounts of sweat, quickly evaluates the contents and beams the data by way of a cellphone to a server that can analyze the results.

Moreover, this test happens all at once and in real time.

The team is now working on large-scale clinical studies to look for correlations between sweat-sensor readings and health.

In the longer term, it’s hoped that the wearable sensor could be integrated into a smartwatch for broad population monitoring.

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