By CAPosts 19 January, 2021 - 09:31am 305 views
could contribute to early detection of COVID-19, even before the onset of symptoms. Subtle changes in the heartbeat, which can be measured with an Apple Watch , can indicate the onset of COVID-19 up to seven days before the infection is diagnosed. That preliminary observation was made by researchers from the Icahn School of Medicine at Mount Sinai as part of the Warrior Watch.
The researchers followed 297 healthcare workers at Mount Sinai Health System between April 29 and September 29. . Participants downloaded a custom app on their iPhones and wore Apple watches. Changes in heart rate variability (HRV), a measure of nervous system function detected by the Apple Watch, were used to identify and predict whether workers were infected with COVID-19
“The watch showed significant changes on HRV metrics up to seven days before people had a positive swab confirming COVID-19 infection and demonstrated significant changes at the time of symptom development, ”said study author Robert P. Hirten, MD, Assistant Professor of Medicine at Icahn School of Medicine at Mount Sinai, in the released statement.
The researchers also identified that seven to fourteen days after diagnosis, the HRV pattern began to normalize and was no longer statistically different from the patterns of those who were not infected
The importance of detecting infection before the onset of any symptoms is that Preventive isolation measures could be taken in these patients. In this way, the spread of hand disease in asymptomatic patients would be reduced.
For its part, Stanford University did a similar study but analyzing not only the use of Apple devices but also products from Garmin, Fitbit and other brands . In this research they identified that 81 percent of patients who tested positive for coronavirus had changes in their resting heart rate up to nine and a half days before the onset of symptoms.
The researchers used data from smart watches to identify nearly two-thirds. of COVID-19 cases four to seven days before people showed symptoms, according to the study published in Nature Biomedical Engineering in November. Within the framework of this research, data from 32 people with coronavirus, from a group of 5,300 participants, will be examined.
“Our findings suggest that activity tracking and health monitoring through consumer wearable devices they can be used for large-scale, real-time detection of respiratory infections, often presymptomatic, ”the report concludes.
The company Whoop, which manufactures sleep-tracking and physical activity-tracking wristbands, partnered with Australia's Central Queensland University to conduct research indicating that its technology can help predict coronavirus infections based on detected deviations in users' respiratory rates during nighttime sleep. The healthy individuals experienced little variability in their respiratory rates, and identified that the modifications suggested a compromise of the respiratory tract.
271 people were analyzed in the report. The model identified 20% of COVID-19 positive patients two days before the onset of symptoms, and 80% of COVID-19 positive cases on the third day of symptoms.
“This study presents a novel method and non-invasive to detect SARS-CoV-2 infection before and during the first days of symptoms. The findings indicate that the early stages of infection may have a detectable signature that could help identify people who should isolate themselves and seek testing, ”the report concludes.
Oura Health, which makes a smart ring which collects data on health indicators , helped fund a study from the University of California, San Diego and the University of California, San Francisco that analyzed information from 50 people. The research concluded that the device can detect subtle symptoms linked to COVID-19, such as the early onset of fever. But it was also noted that this factor alone is not enough to diagnose the disease.
“This work shows the feasibility of collecting fever-related information from distributed populations using portable devices. Our findings also suggest that the success of attempts to identify COVID-19 with specificity of wearables will require multiple physiological variables for its corroboration ”, the study highlights.
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