University of South Florida


Developing a wearable device to detect COVID-19 progression in at-risk patients

A man wearing the noninvasive device being developed to detect the progression of COVID-19

A new study from researchers at the University of South Florida is shedding light on the human body’s physiological response to COVID-19, insight scientists say could help them develop an early warning system for those most at risk of severe infection.

In the United States, the number of cases has surpassed 2 million according to Johns Hopkins University and continues to grow. While the total rate of infection is alarming, the percentage of those patients who experience severe illness from the virus remains relatively low. Experts say certain factors, such as age and health history, appear to play a role in overall outcomes, but USF researchers hope to better understand the differences in physiological changes between those patients who experience severe effects and those who do not.

Shimmer wrist sensor being used in the study

The study will utilize wearable wrist and chest sensor technology from Shimmer Research, Inc., a private company partnering with USF for the study.

“When you look at the viral progression across a population of people, it is very hard to anticipate which people will be severely affected by this virus. There are many different cases of individuals who are otherwise healthy, yet still have a violent reaction,” said principal investigator Matt Mullarkey. “We are confident that by examining certain markers, we can find physiological patterns that can help identify patients who are headed toward serious complications.”

Utilizing existing noninvasive medical monitoring technology, researchers will monitor the physiological conditions of more than 100 study participants, each having tested positive for COVID-19. The wearable device, which is being provided by Shimmer Research, Inc., a private company partnering with USF for the study, will track a variety of markers, including skin temperature, thoracic bioimpedance, oxygen saturation (SpO2) and more. Once the data is collected, scientists will use machine learning and artificial intelligence to synthesize the information and find patterns within the physiological fluctuations. These patterns will then be used to develop various profiles for potential patient outcomes.

Once the physiological profiles are developed, researchers can then use them to identify patients who may be at risk for severe infection.

“We want to give medical professionals and patients as early an indicator as possible, an early warning system if you will, that a particular person, who is normally healthy but who has been exposed to the virus, fits a physiological profile for negative outcomes,” said Dr. Asa Oxner, co-principal investigator of the study. “If we can alert medical professionals early about the viral progression, the hope is they can take the appropriate medical interventions to save lives.”

A man wearing an ECG monitor
A computer showing the ECG reading from the monitor

The study, funded through a USF COVID-19 Rapid Response Grant, brings together a transdisciplinary team of researchers from across the university. Mullarkey is the director of the USF Muma College of Business’s Doctor of Business Administration Program. He is working with Oxner, director of the TGH-USF Health COVID Clinic, colleagues from the USF College of Nursing and in the School of Information, along with the private company supplying the devices. It’s this intersection of disciplines, Mullarkey says, that is one of the strengths of conducting research at USF.

“We’re trying to improve health care outcomes for people all over the United States and the world. So, to have USF put funding behind this initiative proves that we’re willing to put our money behind our science and use that science to create impact. It makes me very proud to be a part of the USF community,” Mullarkey said.

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