The goal of this observational study is to evaluate whether AI-based analyses of wearable sensor data can identify early signs of deterioration leading to hospitalization in patients with advanced heart failure. The main questions it aims to answer are: * Can AI-driven analysis of wearable data detect physiological or behavioral changes associated with impending hospital admissions? * Does wearable-based remote monitoring influence daily exercise duration in patients with advanced heart failure. * Is wearable-based remote monitoring usable and acceptable for patients with advanced heart failure in a real-world setting? Participants will wear a wrist-worn (Fitbit) device continuously for one year and will use an eHealth app to answer question about their symptoms. Participant's physical activity, heart rate, heart rate variability, respiratory rate, sleep quality, and symptomatic status will be monitored remotely.
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Timeframe: From enrollment to the end of the monitoring period at 1 year.