Scientist Invents Hand-Held Breath Monitor to Detect Flu

Simple device would bypass expensive lab equipment

Dr. Perena Gouma, a professor at the University of Texas at Arlington, has published an article in the journal Sensors that describes her invention of a hand-held breath monitor designed to detect the flu virus.

Gouma’s device is similar to the breathalyzers used by police officers when they suspect a driver of being under the influence of alcohol. A patient exhales into the device, which uses semiconductor sensors similar to those in a household carbon monoxide detector. The sensors can isolate biomarkers associated with the flu virus and can indicate whether or not a patient has the flu.

The device could eventually be available in drugstores so that people can be diagnosed earlier and take medications used to treat the flu in its earliest stages, Gouma said.

She and her team studied the medical literature to determine the quantities of known biomarkers present in a person’s breath when he or she is affected by a particular disease. The researchers then applied that knowledge to find a combination of sensors for those biomarkers that can accurately detect the flu virus. For example, people with asthma have increased concentrations of nitric oxide in their breath, and acetone is a known biomarker for diabetes and metabolic processes. When a nitric oxide sensor and an ammonia sensor were combined, Gouma found that the breath monitor could detect the flu virus.

“I think that technology like this is going to revolutionize personalized diagnostics,” she said. “This will allow people to be proactive and catch illnesses early, and the technology can easily be used to detect other diseases, such as Ebola virus disease, simply by changing the sensors.”

She added: “Before we applied nanotechnology to create this device, the only way to detect biomarkers in a person’s breath was through very expensive, highly technical equipment in a lab, operated by skilled personnel. Now, this technology could be used by ordinary people to quickly and accurately diagnose illness.”

Source: University of Texas at Arlington; January 31, 2017.