Real-time alerting system for COVID-19 and other stress events using wearable data.

Early detection of infectious diseases is crucial for reducing transmission and facilitating early intervention. In this study, we built a real-time smartwatch-based alerting system that detects aberrant physiological and activity signals (heart rates and steps) associated with the onset of early infection and implemented this system in a prospective study. In a cohort of 3,318 participants, of whom 84 were infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this system generated alerts for pre-symptomatic and asymptomatic SARS-CoV-2 infection in 67 (80%) of the infected individuals.

A scalable, secure, and interoperable platform for deep data-driven health management.

The large amount of biomedical data derived from wearable sensors, electronic health records, and molecular profiling (e.g., genomics data) is rapidly transforming our healthcare systems.

Real-time Alerting System for COVID-19 Using Wearable Data.

Early detection of infectious disease is crucial for reducing transmission and facilitating early intervention. We built a real-time smartwatch-based alerting system for the detection of aberrant physiological and activity signals (e.g.

Prediction of Stress Map in Ascending Aorta - Optimization of the Coaxial Position in Transcatheter Aortic Valve Replacement.

Backgroud: Transcatheter aortic valve replacement (TAVR) can reduce mortality among patients with aortic stenosis. Knowledge of pressure distribution and shear stress at the aortic wall may help identify critical regions, where aortic remodeling process may occur. Here a numerical simulation study of the influence of positioning of the prosthetic valve orifice on the flow field is presented.