mHealth Wearables, Connected Health Detect COVID-19 Early

Wearable devices can detect COVID-19 cases earlier than traditional diagnostic methods and can provide connected health solutions for providers to manage the disease, according to a Mount Sinai study.

The findings, published in the Journal of Medical Internet Research, reveal that small changes in an individual’s heart rate variability (HRV) measured by an Apple Watch can signal the onset of COVID-19 up to a week before the person is diagnosed via a nasal swab. The Apple Watch’s HRV measure also can identify individuals who have symptoms.

“This study highlights the future of digital health,” said the study’s corresponding author Robert P. Hirten, MD, assistant professor of medicine at the Icahn School of Medicine at Mount Sinai, and member of the Hasso Plattner Institute for Digital Health at Mount Sinai and the Mount Sinai Clinical Intelligence Center (MSCIC).

“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. 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,” Hirten continued.

The ongoing digital study conducted between April and September 2020 involved several hundred healthcare workers throughout the Mount Sinai Health System. The study participants wore Apple Watches and answered daily questions through a customized app.

Researchers collected data on changes in participant HRV to identify and predict whether the workers were infected with COVID-19 or had symptoms. Other daily symptoms that were collected through the app included fever or chills, sneezing, body aches, dry cough, runny nose, diarrhea, sore throat, loss of smell or taste, headache, shortness of breath, tiredness or weakness, and itchy eyes.

The researchers found that one to two weeks after diagnosis with COVID-19, participants’ HRV patterns began to normalize and resembled patterns of those 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,” said the study’s co-author Zahi Fayad, PhD, director of the BioMedical Engineering and Imaging Institute.

Fayard is also co-founder of the MSCIC and the Lucy G. Moses professor of medical imaging and bioengineering at the Icahn School of Medicine at Mount Sinai.

The study was conducted as a collaborative effort by the Hasso Plattner Institute for Digital Health and the MSCIC, a diverse group of professionals who joined together in the spring of 2020 to combat COVID-19.

Next, the study will examine the role biometrics such as HRV, sleep disruption, and physical activity could play in determining which health care workers are most at-risk of the psychological effects of the pandemic.

This is just one of the many studies that have researched the efficacy of connected health devices and platforms to monitor people for COVID-19 symptoms.

Results from a Fitbit study launched in May also revealed that mHealth wearables can help providers identify people infected with COVID-19, sometimes even before symptoms are evident.

Based on data from more than 100,000 Fitbit users on the company’s telehealth platform, almost half of the approximate 1,000 users who developed COVID-19 could be identified as having the virus 24 hours before they started showing symptoms with 70 percent specificity.

Through connected health solutions, experts are creating algorithms to help providers quickly determine individuals who need care. These connected health technologies also allow providers to manage care for those with COVID-19 and keep them isolated, either in a hospital or in their home.