UCLA
Sam Emaminejad has been working on a wearable sensor that can extract sweat by applying an electrical current to the skin and then analyzing its molecular components, such as chloride ions and glucose, to detect certain diseases.

Sam Emaminejad, assistant professor of electrical engineering at UCLA, has demonstrated that a wearable biosensor can be used in the diagnosis of cystic fibrosis, diabetes and other diseases by measuring molecules present in an individual's sweat.

He developed the biosensor with colleagues while he was a joint postdoctoral researcher at Stanford Medicine and UC Berkeley. Currently, he is completing his first year on the UCLA engineering faculty and is continuing this line of research in his lab.

The key to the biosensor is it “activates” your sweat while you wear it and you don’t have to run up stairs or stay on a treadmill to the point where you break out in sweat. The research demonstrated for the first time that a wearable, non-invasive sensor can extract sweat at the skin’s surface and monitor in real time important biomarkers for patients.

Emaminejad spoke recently to UCLA Engineering writer Matthew Chin about his research and teaching goals.

 What can sweat tell about what’s going on inside us? And why hasn’t sweat been used much for patient monitoring and tracking?

Sweat is a rich source of physiological information and contains many biomarkers such as metabolites, electrolytes  and proteins that can inform us of our health status.

Sweat-based monitoring has a huge potential to facilitate non-invasive and continuous monitoring of individuals in a wearable format, such as a smartwatch. For robust analysis we need a few droplets of sweat on demand, which is not really accessible unless we exercise or lock ourselves in sauna!

In the work that just came out, we demonstrated a platform that can stimulate sweat glands to produce sweat with the aid of an electrical current.

In other words, [patients] don’t have to work up a sweat, or feel discomfort to get at this valuable source of physiological information. This is an unprecedented opportunity, because now a previously inaccessible source of information has been made available for real-time monitoring.

What is the long-term vision for your research? 

The Interconnected and Integrated Bioelectronics Lab was established [at UCLA] to bridge the gap between the two worlds of Internet of Things and personalized medicine, through the development of an ecosystem of integrated and interconnected mobile, wearable and in-vivo health monitoring platforms.

These platforms facilitate the analysis of biomarker content in various human biofluids such as blood, sweat, saliva and urine, in combination with continuous measurement of physiological signals to provide a comprehensive and dynamic view of our health states.

Realizing this vision requires resolving major bottlenecks from various fronts, and we work closely with experts in biology, medicine and data science to optimize our efforts toward high impact applications. In that regard, UCLA is the perfect place for leading this collaborative research program, given the excellent synergy between the engineering and medical schools.

Courtesy of Sam Emaminejad
A wearable sweat sensor can be used for diagnosing and monitoring diseases in real time.

You’re teaching a class this spring quarter of your own design (EE 279 AS Micro- and Nanoscale Biosensing for Molecular Diagnostics) based on one that you co-developed and taught while a graduate student and post-doc. What does it cover, and what do you hope students get out of it?

I believe to exponentially amplify our efforts toward achieving our research vision, it is crucial to also focus on raising the next generation of researchers who ... can take the lead in resolving the challenges ahead.

The goal of this course is for students to appreciate the interface of biology and engineering and to be equipped with the critical thinking and problem-solving skills necessary to evaluate and propose solutions for today’s most pressing biosensing problems.