Is sweat the future of wearable medical devices?

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Sweat contains a wealth of biological information that, with the help of artificial intelligence (AI) and next-generation sensors, could transform how we monitor our health and wellbeing, a new study suggests.

The study, published in the Journal of Pharmaceutical Analysis, examines sweat’s potential for real-time monitoring of hormones and other biomarkers, medication doses, and early detection of diseases such as diabetes, cancer, Parkinson’s, and Alzheimer’s.

“Collecting sweat is painless, simple, and non-invasive,” says co-author Dr. Dayanne Bordin, an analytical chemist at the University of Technology Sydney (UTS). “It’s an attractive alternative to blood or urine, especially for continuous monitoring in real time.”

“Anyone who is already interested in tracking their health using wearables such as an Apple watch – for example their heart rate, step count, or blood pressure – would be interested in the information sweat can provide.

“There are already sweat monitoring devices on the market such as the Gatorade sweat patch, which is a single-use, wearable sticker that pairs with an app to analyze your sweat rate and sodium loss, and provide tailored advice.”

Recent advances in microfluidics, stretchable electronics, and wireless communications have led to a new generation of wearable sensors. These thin, flexible patches adhere to the skin and continuously sample sweat.

Combined with AI, these devices could detect specific metabolites and interpret complex biochemical patterns, offering users personalized health insights and early warning for a range of diseases.

Athletes could monitor electrolyte loss during training and provide proof they’re drug free before competitions. Diabetic patients might one day wear a patch detecting glucose changes through sweat instead of blood tests.

“Sweat is an under-used diagnostic fluid,” says co-author Dr. Janice McCauley from the UTS Faculty of Science.

“The ability to measure multiple biomarkers simultaneously, and transmit that data wirelessly, provides enormous potential for preventive health care.

“The year 2023 was marked by an evolutionary step in artificial intelligence, opening the door for improved pattern analysis and classification algorithms to improve diagnostic precision and therapeutic accuracy,” she says.

AI can now process huge datasets to link subtle molecular signals in sweat to specific physiological states. The next step, the authors suggest, is integrating this with compact, low-power devices with secure data transmission.

UTS researchers are currently working on understanding the baseline physiological aspects of sweat. They’re also developing microfluidic devices sensitive enough to detect trace amounts of biomarkers such as glucose and cortisol.

While much of the research remains at the prototype stage, commercial interest is growing.

“We’re not far from a future where your wearable can tell you when you’ve got high stress hormone levels, and by monitoring this over time, whether you are at risk of chronic health conditions,” Dr. Bordin says.

University of Technology Sydney
https://www.uts.edu.au