A team of researchers announced recently that by analyzing biometric data from a wearable device, they believe they can detect the onset of the COVID-19 virus’ symptoms in seemingly healthy individuals as much as three days in advance.
As TechCrunch reports, the study was conducted by researchers from the West Virginia University (WVU), Rockefeller Neuroscience Institute (RNI), staff from Oura Health (makers of the Oura Ring), and members of WVU’s Medicine department.
The study took biometric data that was collected from participants who wore an Oura Ring — a smart ring that uses biometric sensors to track metrics such as body temperature, sleep patterns, and heart rate — and compared it against physiological, cognitive and behavioral biometric data from roughly 600 first responders and healthcare workers.
After comparing and combining these datasets, the research team used them to develop an artificial intelligence-based model designed to anticipate the onset of symptoms before they manifested. Though it is important to keep in mind that these results come from a phase-one study and have yet to be peer-reviewed, the fact that the model showed a 90% accuracy rate in predicting the symptoms — coughing, fever, and fatigue among them — is encouraging.
The ability to predict symptoms with accuracy and identify individuals who are potential carriers of COVID-19 could result in earlier testing, which in turn could go a long way in slowing the spread of the virus.
The research team says that the next step for the study is to expand it across a number of states, and include different academic partners and institutions, with the aim of reaching up to 10,000 participants.
(Originally posted on FindBiometrics)