Wearable Multiplexed Biosensor to Guide Exercise in Patients with Heart Failure

This project focuses on the application of wearable technology and machine learning to improve the management of patients with heart failure.

The major goals of this research are to use machine-learning approaches to identify high-risk features that manifest during exercise in patients with heart failure and to develop a wearable sweat sensor capable of identifying these high-risk physiological features during exercise.

The combination of wearable biosensor technology and advanced analytical methods aims to provide real-time insights and guidance, ultimately enhancing the safety and effectiveness of exercise regimens for individuals managing heart failure.

Contact PI: Alex Bui; Jeffrey John Hsu (UCLA)

Funding Source:  AHA