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Study: Apple Watch To Help Detect Covid19 Symptoms

The study highlights the future of digital health

It seems the Apple Watch that you wear can help detect even Covid-19 as researchers have found that the device can identify such cases earlier than traditional diagnostic methods and can help track and improve management of the disease.

The study by researchers at Mount Sinai hospital in the US found that subtle changes in a participant’s heart rate variability (HRV) measured by an Apple Watch were able to signal the onset of Covid-19 up to seven days before the individual was diagnosed with the infection via nasal swab, and also to identify those who have symptoms.

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“This study highlights the future of digital health,” said the study’s corresponding author Robert Hirten, Assistant Professor at the Icahn School of Medicine at Mount Sinai. “It shows that we can use these technologies to better address evolving health needs, which will hopefully help us improve the management of the disease.”

Hirten said that developing a way to identify people who might be sick even before they know they are infected would be a breakthrough in the management of Covid-19. The researchers enrolled several hundred health care workers throughout the Mount Sinai Health System in an ongoing digital study between April and September 2020. The participants wore Apple Watches and answered daily questions through a customized app.

Apple watc
Covid19. Pixabay

Changes in their HRV – a measure of nervous system function detected by the wearable device – were used to identify and predict whether the workers were infected with Covid-19 or had symptoms. Other daily symptoms that were collected included fever or chills, tiredness or weakness, body aches, dry cough, sneezing, runny nose, diarrhea, sore throat, headache, shortness of breath, loss of smell or taste, and itchy eyes.

ALSO READ: New Device Uses Apple Watch to Reduce Nightmare Disorder

Additionally, the researchers found that 7 to 14 days after diagnosis with Covid-19, the HRV pattern began to normalize and was no longer statistically different from the patterns of those who were not infected, according to the findings published in the Journal of Medical Internet Research.

“This technology allows us not only to track and predict health outcomes but also to intervene in a timely and remote manner, which is essential during a pandemic that requires people to stay apart,” said the study’s co-author Zahi Fayad, Professor at the Icahn School of Medicine at Mount Sinai. (IANS)

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