Containing the COVID-19 pandemic requires rapidly identifying infected individuals. Subtle
changes in physiological parameters (such as heart rate, respiratory rate, and skin …

Wearable technology is an emerging method for the early detection of coronavirus disease
2019 (COVID-19) infection. This scoping review explored the types, mechanisms, and …

Background Longitudinal digital health studies combine passively collected information from
digital devices, such as commercial wearable devices, and actively contributed data, such …

Detailed mobile sensing data from phones and fitness trackers offer an opportunity to
quantify previously unmeasurable behavioral changes to improve individual health and …

Objectives We investigated machinelearningbased identification of presymptomatic COVID-
19 and detection of infection-related changes in physiology using a wearable device …

Importance Currently, there are no presymptomatic screening methods to identify individuals
infected with a respiratory virus to prevent disease spread and to predict their trajectory for …

Consumer-grade wearables are needed to track disease, especially in the ongoing
pandemic, as they can monitor patients in real time. We show that decomposing heart rate …

Goal: To investigate whether a deep learning model can detect Covid-19 from disruptions in
the human body's physiological (heart rate) and rest-activity rhythms (rhythmic …

The timely identification of infectious pre-symptomatic and asymptomatic cases is key
towards preventing the spread of a viral illness like COVID-19. Early identification has been …

Algorithms for the detection of COVID-19 illness from wearable sensor devices tend to
implicitly treat the disease as causing a stereotyped (and therefore recognizable) deviation …