The West Virginia University Rockefeller Neuroscience Institute (RNI), WVU Medicine, and smart ring maker Oura Health are collaborating on a study designed to accelerate early detection of the COVID-19 virus symptoms and contagiousness.
Leveraging an artificial intelligence (AI)-driven predictive model, wearable ring technology, and a COVID-19 monitoring app, RNI scientists and partners are developing a “digital PPE” approach that potentially can identify infected frontline healthcare professionals before they become symptomatic. Researchers believe this is a possible breakthrough in monitoring capabilities and limiting the spread.
The RNI’s approach doesn’t just measure the onset of increased body temperature from the Oura ring and physical symptoms, but looks at the individual holistically – integrating physiologic measures with psychological, cognitive and behavioral biometrics, such as stress and anxiety, officials stated.
“In real-time, this holistic approach can provide an early and more comprehensive assessment, tracking the mind-body connection and homeostasis in the context of asymptomatic infection. Through this analysis, the team can forecast and predict the onset of fever, cough, fatigue and other physical symptoms linked to viral infections,” officials contend.
The International Council of Nurses (ICN) has been tracking infected healthcare workers across the globe, and has reported that tens of thousands of cases can be attributed to this population segment.
Over the past few weeks, Oura smart rings and the RNI COVID-19 monitoring smartphone app have been deployed to physicians, nurses and other frontline healthcare workers in the ED, ICU, testing sites, and urgent care settings in West Virginia. In addition, the RNI is partnering with hospitals across the country, including those in New York City, Philadelphia, Nashville and other critical emerging areas, to monitor more than 1,000 front-line healthcare personnel with exposure to COVID-19, according to officials.
“We are continuously monitoring the mind-body connectivity through our integrated neuroscience platform measuring the autonomic nervous system, fatigue, anxiety, circadian rhythms, and other human resilience and recovery functions,” Ali Rezai, M.D., executive chair of the WVU Rockefeller Neuroscience Institute, said in a statement. “Our AI-driven models are currently predicting symptoms 24 hours prior to onset, and we are working toward a three-plus day forecast. This forecasting capability will help us get ahead of this pandemic; limit the spread to protect healthcare workers, their families, and our communities; and improve our understanding of health recovery.”
