AI-Based Monitoring System for Chronic Heart Failure With Advanced Wearable and Mini-Invasive Devices

The goal of this observational, multicenter study is to evaluate whether AI-driven remote monitoring using a mini-invasive wearable device can improve clinical outcomes in adult patients (≥18 years) with chronic heart failure (CHF). The main questions it aims to answer are: * Can continuous remote monitoring reduce hospital admissions (emergency visits and hospitalizations) by 20% compared to standard care? * Does wearable-based remote monitoring improve functional, biochemical, and instrumental parameters in CHF patients? Researchers will compare patients using the wearable device (intervention group) to those receiving standard clinical follow-up (control group) to assess whether AI-driven monitoring leads to fewer hospitalizations, better disease management, and improved quality of life. Participants will: * Wear the EmbracePlus (Empatica Inc.) device continuously for six months (intervention group only). * Have their biometric data (SpO₂, HRV, EDA, respiratory rate, temperature, sleep quality) monitored remotely. * Receive automated alerts and teleconsultations if abnormal physiological changes are detected. * Attend scheduled follow-up visits (remote and in-person) for clinical evaluation and treatment adjustments. The study aims to provide real-world evidence on whether integrating wearable health technology with AI analytics can enhance CHF management and improve patient outcomes.

This description comes directly from the study's public registry record.

Alessia Bramanti, Electronic Engineering  ·  +393483809181  ·  abramanti@unisa.it

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