A breakthrough in COVID-19 management would be developing a mechanism to identify people who may be sick even before they realize they are infected.
Wearable gadgets, according to a recent study, can help detect COVID-19 cases earlier than standard diagnostic methods, as well as track and optimize disease management.
The study discovered that small variations in a participant’s heart rate variability (HRV) monitored by an Apple Watch may predict the beginning of COVID-19 up to seven days before a nasal swab diagnosis, as well as identify those who had symptoms.
“This study highlights the future of digital health,” according to the study’s corresponding author Robert P. Hirten. “It shows that we can use these technologies to better address evolving health needs, which will hopefully help us improve the management of disease. Our goal is to operationalize these platforms to improve the health of our patients and this study is a significant step in that direction.”
Between April and September 2020, the researchers enrolled several hundred health care employees across the Mount Sinai Health System in an ongoing digital study.
The subjects wore Apple Watches and responded to daily questions via a special app. HRV, a measure of nervous system function sensed by the wearable device, was used to identify and predict whether the workers were infected with COVID-19 or experienced symptoms.
Fever or chills, exhaustion or weakness, body aches, dry cough, sneezing, runny nose, diarrhea, sore throat, headache, shortness of breath, loss of smell or taste, and itchy eyes were among the other daily symptoms collected.
Furthermore, the researchers discovered that 7 to 14 days following COVID-19 diagnosis, the HRV pattern began to normalize and was no longer statistically different from individuals who were not infected.
“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,” adds the study’s co-author Zahi Fayad.
The researchers will then look at biometrics like HRV, sleep disruption, and physical activity to see which healthcare employees are more vulnerable to the pandemic’s psychological consequences.
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