International Multi-center Study to Validate an Early Warning Algorithm for Worsening Heart Failure

The study is a multi-center, prospective, non-randomized, observational study to collect data to develop and validate a machine learning algorithm for early detection of worsening heart failure events using multi-parametric sensor data from wearable data capture device The VESTA study will enroll up to 552 subjects in up to 25 centers in order to collect data on a total of at least 56 worsening heart failure events (independently adjudicated hospitalizations or unscheduled intravenous administration of decongestive drugs).The duration of follow-up per participant will be between 3-6 months.