Smart ring that constantly measures your temperature could provide early warning for Covid-19

A smart ring that constantly monitors your temperature can help you determine if you develop Covid-19, even if your symptoms are very vague.

Experts from the University of California and MIT Lincoln Lab examined data from 50 people who had contracted Covid-19 who had sensor rings before the study.

This was the first study to publish data from a project by a Finnish startup called TeamPredict, a study that recorded the temperature, heart rate, respiratory rate, and activity levels of more than 65,000 people who wore Oura rings.

They found that the ring temperature data can be used reliably to detect the early onset of fever, the leading symptom of Covid-19 and flu.

They cautioned that the study was a proof-of-concept study with only 50 participants, adding that more data is needed to understand whether it is a reliable tool for detecting the virus.

Study author Benjamin Smarr and colleagues found that the onset of fever occurred before a person reported symptoms and in those who had never reported symptoms.

“It supports the hypothesis that some febrile events are not reported or detected until they are truly asymptomatic,” the researchers write.

“Wearable devices can help identify asymptomatics” [illness] Unlike unreported diseases, [which is] It is of particular importance in the COVID-19 pandemic”.

The goal of the larger TeamPredict survey of 65,000 people wearing Oura rings is to develop an algorithm that can predict the onset of Covid-19 symptoms.

Researchers say they hope to reach that target by the end of the year, which will allow public health officials to act more quickly to contain the spread of the virus.

“It’s not just a scientific problem, it’s a social problem,” Smarr says.

“With wearable devices that can measure temperature, we can imagine a public COVID early warning system.”

Smarr said they need users from different backgrounds to share their data to develop an effective algorithm.

The data is stripped of all personal information, including location, and each individual is identified by a random identification number instead of name or personal details.

Ashley Mason, a professor in the department of psychiatry and the Osher Center for Integrative Medicine at UC San Francisco, is the study’s principal investigator.

The researchers found that data from Oura ring carriers with Covid-19 showed spikes in temperatures (red areas) indicating fever, even before symptoms were reported.

“If wearable devices allow us to detect COVID-19 early, people can start practicing physical isolation and undergo testing to reduce the spread of the virus,” Mason said. Said.

“For example, an ounce of prevention may be worth even more than a pound of cure.”

Wearables like the Oura ring continuously collect temperature data day and night, allowing researchers to measure people’s true core temperatures and more accurately determine fever spikes.

“The temperature varies not only from person to person, but at different times of the day for the same person,” Smarr said.

The study highlights the importance of collecting data continuously over long periods rather than on-site data collection.

Meanwhile, Smarr explained that the reason why temperature controls are not effective in detecting COVID-19 is the continued lack of data.

These examples are the equivalent of catching one syllable per minute in a speech rather than whole sentences, he said.

All 50 subjects in the study had Oura rings and had COVID-19 prior to coming to TemPredict.

They provided summaries of the symptoms of their disease and gave researchers access to data collected by the Oura rings during their illness.

The signal for the onset of fever isn’t subtle, Smarr said. “The map that followed the hot people seemed to be on fire.”

Data collected as part of this and subsequent TeamPredict study will be archived at the San Diego Supercomputer Center.

“The data collected has great potential to connect with other datasets that provide a combination of individual and social scale models to better understand the disease,” said Ilkay Altintas of the San Diego Supercomputer Center.

Researchers are also continuing their efforts to recruit a diverse set of subjects that reflect the American population.

“We need to make sure our algorithms work for everyone,” Smarr said.

In the future, the researchers plan to expand early detection methods to include other infectious diseases such as influenza.

The results are published in Scientific Reports.