Scientist invents breath monitor to detect flu
Perena Gouma, a professor in the UTA Materials Science and Engineering Department, has published an article that describes her invention of a hand-held breath monitor that can detect the flu virus.
Gouma’s device is similar to the breathalysers used by police officers when they suspect a driver of being under the influence of alcohol. A patient simply exhales into the device, which uses semiconductor sensors like those in a household carbon monoxide detector.
The difference is that these sensors are specific to the gas detected, yet still inexpensive, and can isolate biomarkers associated with the flu virus and indicate whether or not the patient has the flu. The device could eventually be available in drugstores so that people can be diagnosed earlier and take advantage of medicine used to treat the flu in its earliest stages. This device may help prevent flu epidemics from spreading, protecting both individuals as well as the public health.
Gouma and her team relied on existing medical literature to determine the quantities of known biomarkers present in a person’s breath when afflicted with a particular disease, then applied that knowledge to find a combination of sensors for those biomarkers that is accurate for detecting the flu. For instance, people who suffer from asthma have increased nitric oxide concentration in their breath, and acetone is a known biomarker for diabetes and metabolic processes. When combined with a nitric oxide and an ammonia sensor, Gouma found that the breath monitor may detect the flu virus, possibly as well as tests done in a doctor’s office.
Gouma’s sensors are at the heart of her breath analyser device.
‘I think that technology like this is going to revolutionize personalized diagnostics. 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,’ said Gouma, who also is the lead scientist in the Institute for Predictive Performance Measurement at the UTA Research Institute.
The University of Texas at Arlington http://tinyurl.com/y7tfoy5e
