Duke researchers to collect biometrics from wearables in search for early COVID-19 detection method
Do smartphones and biometric wearables already contain the data we need to know if we have become infected with the novel coronavirus? A team of research scientists from Duke University intend to find out, through their new CovIdentify project, according to an article published by Duke’s Pratt School of Engineering.
Health information from smartphones, smartwatches and fitness wearables, such as sleep schedules, oxygen levels, activity levels and heart rate will be analyzed to determine if they can help detect early symptoms of COVID-19. Participants can sign up at Covidentify.org, where they begin by answering survey questions, as in other initiatives like Flatten.ca.
Currently, data is only connected from Fitbits, but the team plans to launch a CovIdentify iOS app to pull data from any device synced with the Apple Health app, with launches for Android and Google devices to follow. All health data is protected and kept anonymous, according to the report. Continuous biometric data will be gathered from participants, which paired with daily surveys may reveal any relationship between the biometric data and symptoms.
The goal of the project is to collect 12 months of historical data and six months of data going forward, enabling the creation of a baseline understanding of normal health characteristics, and the trajectory of the illness.
The project is led by Assistant Professor of Biomedical Engineering Jessilyn Dunn and Associate Professor of Nursing and Health Innovation Lab Director Ryan Shaw.
“We anticipate a great convergence of wearable data, self-reported symptoms, molecular testing and geospatial data to help us manage infections and outbreaks,” says Geoff Ginsburg, M.D., who is the director of MEDx (Medicine and Engineering at Duke), who is collaborating with Dunn and Shaw. “CovIdentify is at the leading edge of this convergence.”
“One of my lab’s goals is to arm health care professionals with tools and information to detect illness and intervene early by delivering the right treatment to the right person at the right time,” Dunn comments. “If this study is successful, we’d be able to use non-invasive and accessible tools to help us control the spread of a dangerous virus, and predict when someone may need more intensive care. If we can achieve this, we may be able to help doctors save more lives.”
Ginsburg and a collaborator also have research project ongoing related to early detection of disease with wearables, supported by the Defense Advanced Research Project Agency (DARPA).
A similar national research project involving Oura Rings and front-line healthcare providers was recently launched by West Virginia University.
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