Biohazard breathalyzer could detect coronavirus

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On August 4, 2020

Dr. Rex E. Gerald II (left) and Dr. Jie Huang (right) are working to develop an airborne-biohazard system that could help screeners spot air travelers with lung diseases due to coronavirus and other viruses.

S&T electrical and computer engineering researchers are using machine learning to build a system to alert authorities to airborne biohazards such as the coronavirus as travelers pass through airport security checkpoints.

“The mission of this lab is to invent sensors that have ultra-high sensitivity,” says assistant professor Jie Huang. “We are advancing new frontiers in research.”

To trigger the airborne-biohazard alert system, individuals would exhale into a sensor Huang’s team is developing to detect viruses in the breath. If a virus is detected, the breath would be chemically tagged for further testing in a spectrometer. The entire process would take less than a minute and could eventually differentiate between a cold, flu or coronavirus. The researchers hope the system could be made widely available in accessible locations so people could self-test, similar to blood pressure monitors in retail stores.

“This could provide valuable information to the individual, done in private of course,” says visiting professor Rex E. Gerald. “We focused on airports first to try to mitigate the impact of canceled flights in the event of a pandemic, which could cost billions of dollars to the airline industry.”

With each iteration of the prototype device, the team provided researchers in biology, chemistry and medicine an opportunity to evaluate the evolving design of the sensor system. The researchers adjust and modify the system based on their feedback. 

The front-end sensor, which would indicate whether someone is sick or healthy, could be ready for clinical trials in about a year. The full system with chemical tagging and a spectrometer will take significantly longer to develop.

The biohazard sensor showcases the types of research that complement the University of Missouri System’s NextGen Precision Health Initiative, which is expected to accelerate medical breakthroughs by harnessing the research expertise of the four UM System universities.

Working with Huang and Gerald are lead graduate student Chen Zhu, assistant research professor Qingbo Yang and artificial intelligence expert Donald Wunsch, the Mary K. Finley Distinguished Professor of Computer Engineering.

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On August 4, 2020. Posted in 2020, Around the Puck, Research, Summer 2020