Oura Ring Detects Fever, A Common Symptom of COVID-19

Oura Ring Detects Fever, A Common Symptom of COVID-19 - Before It Occurs

Wearables predict illness early using temperature data, finds Scientific Reports study.

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Image: Oura

Wearables can predict the onset of illnesses using longitudinal temperature data even before symptoms appear, according to new research published in the journal Scientific Reports.

The study showed that temperature data collected by Oura ring detected the onset of fevers, a leading symptom of both COVID-19 and the flu, according to a team of researchers from the University of California San Diego, UC San Francisco and MIT Lincoln Lab.

The Scientific Reports paper is the first published result from TemPredict, a study of more than 65,000 people wearing a ring manufactured by Finnish startup Oura, that records temperature, heart rate, respiratory rate and levels of activity. The goal of the study is to develop an algorithm that can predict the onset of symptoms such as fever, cough, and fatigue, which are characteristic of COVID-19. Researchers say they hope to reach that goal by the end of the year. They also hope the algorithms will allow public health officials to act faster to contain the virus’ spread, reports UC San Diego News Center.

“This isn’t just a science problem, it’s a social problem,” said Benjamin Smarr, the paper’s corresponding author and a professor in the Department of Bioengineering and the Halicioglu Data Sciences Institute at UC San Diego. “With wearable devices that can measure temperature, we can begin to envision a public COVID early alert system.”

The 50 subjects in the study all owned Oura rings and had had COVID-19 before joining TemPredict. They provided symptom summaries for their illnesses and gave researchers access to the data their Oura rings had collected during the period when they were sick. The signal for fever onset was not subtle, Smarr said. “The chart tracking people who had a fever looked like it was on fire.”

Smarr is TemPredict’s data analytics lead. Ashley Mason, a professor in the Department of Psychiatry and the Osher Center for Integrative Medicine at UC San Francisco, is the principal investigator of the study.

Researchers believe that the best algorithms to predict onset of COVID-19 will compare many variables, and won’t rely on just one signal. By looking at how temperature changes over time and comparing it to heart rate, heart rate variability and respiration rate at the same times, researchers determined that while most fever episodes correspond to changes in other variables too, it’s not a clean 1:1 match: sometimes the heart rate is up, but not the temperature, and vice versa. More variables gives a clearer picture, allowing detection to be precise across disease manifestations. (UC-San Diego)

“If wearables allow us to detect COVID-19 early, people can begin physical isolation practices and obtain testing so as to reduce the spread of the virus,” Mason said. In this way, an ounce of prevention may be worth even more than a pound of cure.”

Wearables such as the Oura ring can collect temperature data continuously throughout the day and night, allowing researchers to measure people’s true temperature baselines and identify fever peaks more accurately. “Temperature varies not only from person to person but also for the same person at different times of the day,” Smarr said.

The study, he explains, highlights the importance of collecting data continuously over long periods of time. Incidentally, the lack of continuous data is also why temperature spot checks are not effective for detecting COVID-19. These spot checks are the equivalent of catching a syllable per minute in a conversation, rather than whole sentences, Smarr said.

In the Scientific Reports paper, Smarr and colleagues noticed that fever onset often happened before subjects were reporting symptoms, and even to those who never reported other symptoms. “It supports the hypothesis that some fever-like events may go unreported or unnoticed without being truly asymptomatic,” the researchers write. “Wearables therefore may contribute to identifying rates of asymptomatic [illness] as opposed to unreported illness, [which is] of special importance in the COVID-19 pandemic.”