Knowing that you are getting sick, for example due to COVID-19, before presenting symptoms could be possible thanks to your smart wristwatch. It sounds like science fiction, but it could be possible thanks to a new algorithm created by members of Standford Medicine (USA), which, thanks to the measurements of the heart rate of these devices, can know the physiological and mental stress of the person who takes it and know if they are getting sick too early.
The research, published in the journal Nature Medicine, has included the participation of 2,155 participants who wore a smart watch that was capable of tracking mental and physical stress events through alterations in heart rate, which when it is higher than normal can be a telltale sign that something may be wrong. When the bracelet detected this stressful situation, it asked the person to enter the activity they were carrying out into the application.
Of the 84 participants who had a positive diagnosis of COVID-19, the algorithm was able to detect 67 of them. Most of the alerts were associated with other causes, such as air travel, having eaten large meals, having menstruation, mental stress, intoxication or infections not caused by SARS-CoV-2. The algorithm also warned of a period of stress after many participants received the COVID-19 vaccine, which could be due to the increased immune response generated by the injection.
The algorithm detects 80% of COVID-19 cases
The results after an eight-month follow-up indicated that the algorithm together with smart watches were able to detect 80% of confirmed cases of COVID-19 before or during the first symptoms. However, the researchers have also stated that the algorithm must be improved, since it seems that it is not capable of differentiating, for example, work stress from someone who is sick, so we still have to be cautious with its practical use.
“The idea is that people will eventually use this information to decide if they need to get tested for COVID-19 or self-isolate.”
“The idea is that people will eventually use this information to decide if they need to get tested for COVID-19 or self-isolate. We haven’t gotten to that point yet, we still need to test this in clinical trials, but that’s the ultimate goal,” explains Michael Snyder, one of the study’s lead authors.
Proposed improvements to the algorithm focus on adding data such as sleep patterns, data counts, and body temperature, which would help better determine different types of stress. If this technique is improved, the researchers believe their algorithm could reliably detect COVID-19 before symptoms appear and could be used to guide clinicians in patient decisions.
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