Wei Gao at Caltech’s Braun Athletic Center.
The Science of Sweat: An Interview with Wei Gao
New Caltech faculty member Wei Gao is interested in the future of personalized and precision medicine, and is engineering the next generation of wearable health monitors and nanomachines that could enable rapid and hyper-localized drug delivery and surgery. Originally from China, Gao received his bachelor’s degree in mechanical engineering from Huazhong University of Science & Technology and his master’s in precision instruments from Tsinghua University. In 2014, he earned a doctorate in chemical engineering at UC San Diego, and then moved up to the Bay Area for a postdoctoral fellowship at UC Berkeley. At the age of 31, Gao was selected for MIT Technology Review’s 2016 list of “35 Innovators under 35” for his development of a wearable health monitor that tracks indicators of health by analyzing sweat. The device has a thin, flexible circuit board that can detect changes in glucose and lactate levels based on fluctuations in electrical current through sweat. We caught up with Gao recently to discuss his career and research.
How did you get into engineering?
It’s a long story. I was born in a small village in China, and when I was a child, I saw people around me pass away from different diseases. They didn’t realize they were sick until it was too late to get help, and it made me want to build devices that could monitor health and maybe save people’s lives. One of the things that inspired me was the movie Fantastic Voyage. It showed scientists and engineers piloting a submarine into a man’s body to save his life. That’s the thing that drove me into the field of nanorobotics.
What brought you to Caltech?
Caltech is internationally known to have high-quality research facilities and very strong science and engineering programs. Most importantly, at Caltech I know I can interact with first-class faculty members, students, and postdoc scholars. Finally, I can see the unique opportunities with the new Andrew and Peggy Cherng Department of Medical Engineering in the Division of Engineering and Applied Science. I feel this new department will be the perfect place for me to perform my interdisciplinary and translational research on bioelectronic devices.
What makes your sweatband health tracker different than any other fitness tracker?
If you look at what is commercially available, you find devices that are capable of providing information on heartbeat and number of steps taken, but they are not capable of studying your health at a molecular level. By analyzing your sweat, my device can give you detailed information about what’s going on inside your body.
Gao’s wearable health monitor
Credit: Courtesy of Wei Gao
What type of information do your sweatbands provide? If I was wearing one right now, how would I use that information?
For example, we can monitor your dehydration level or your blood glucose level in real time. So, during a workout, I could check it and see that perhaps I should be drinking more water or maybe I need to pause for a snack.
What got you thinking about studying sweat in the first place?
I think that sweat is a very important bodily fluid and one that can be retrieved noninvasively unlike, for example, blood. But it still contains many important biomarkers that allow us to extract useful information from it.
Would I need to be exercising and dripping with sweat in order for your sensors to have enough sweat to work with?
Physical exercise isn’t the only way to generate sweat—it can also be generated through heat and through an electrical current via a process called iontophoresis. We have recently built an integrated wearable system that can perform on-demand sweat extraction and analysis. You can wear our device like a watch and, through your cell phone, tell it to manually induce sweat through iontophoresis.
Where is your sensor at in the development process, and what’s next?
We are developing new wearable sensors and performing large-scale population studies right now to study the correlation between biomarkers in sweat and different health conditions. We hope to build a predictive algorithm for different health conditions. For each health condition, we expect to use multiple health biomarkers. For example, we could provide information for diabetics about their glucose levels by measuring the skin temperature and also by the sweat pH, which is why we need to build an integrated sensor array to perform perspiration analysis.
Written by Robert Perkins
source: California Institute of Technology