Smartwatches have become trendy wearables today with greater number of users relying on it for tracking daily activities, fitness and even routine health tests like blood work and ECG.
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Researchers at Stanford University have devised an algorithm to detect stress and signs of prolonged illnesses in smartwatch wearers using data from the device. It is also effective in detecting signs of COVID-19 disease, according to the team.
The system reads heart rate as a proxy for physiological or mental stress, potentially alerting wearers they are falling ill before they see symptoms, the researchers noted in a study titled ‘Real-time alerting system for COVID-19 and other stress events using wearable data’.
The team enrolled over 2,000 participants in a study that employed the algorithm to look for extended periods when heart rate is higher than normal — a sign that something might be amiss.
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The participants wore a smartwatch that tracked physical and mental stress events via heart rate. When notified of a stress event, through an alert via an app on their phone, participants recorded what they were doing like jogging, traveling, hearing a sudden loud noise, eating a large meal, or even menstruating.
The algorithm was also able to detect 80% of confirmed COVID-19 cases before or when the participants were symptomatic, the team noted. It also flagged a period of stress after many participants received a COVID-19 vaccine, reflecting the uptick in immune response prompted by the shot.
“The idea is for people to eventually use this information to decide whether they need to get a COVID-19 test or self-isolate,” the paper added.
