Remote monitoring in patients with heart failure and comorbidities

Heart failure (HF) remains a major public health burden, associated with high morbidity, frequent hospitalizations, and poor prognosis despite advances in pharmacological and device-based therapies. A key limitation in management is the delayed recognition of decompensation episodes, which has prompted the development of remote monitoring (RM) strategies aimed at earlier detection and timely intervention. This thesis investigates innovative RM approaches with a focus on non-invasive, wearable technologies. The first section critically reviews the evolution of RM, from early telemonitoring systems to invasive hemodynamic sensors, multiparametric algorithms embedded in implantable devices, and wearable technologies. The second section addresses non-invasive assessment of pulmonary congestion. A feasibility study using MySIGN, a wearable thoracic belt developed at the University of Bologna, demonstrated reliable acquisition of multiparametric cardio-respiratory signals in healthy volunteers and identified impedance variation as a promising surrogate of pulmonary fluid status. The third section explores acoustic monitoring. Comparative testing of microphone technologies showed that MEMS-based sensors offer the best performance for wearable integration. Preliminary auscultation studies confirmed their ability to capture clinically relevant heart sounds. The fourth section evaluates photoplethysmography (PPG) for hemodynamic monitoring. PPG-derived heart rate variability parameters showed moderate correlation with ECG-based measures, while vascular aging indices were significantly impaired in atrial fibrillation, a frequent HF comorbidity. The fifth section focuses on simplified electrocardiographic monitoring. A modified six-lead ECG configuration, obtained by repositioning limb electrodes to approximate V1 and V6, accurately estimated ventricular activation times in patients undergoing conduction system pacing, supporting its feasibility for streamlined remote follow-up. Finally, these insights converge in REMEDY, a next-generation Internet-of-Medical-Things platform built around a modular, adhesive wearable incorporating ECG, bioimpedance, acoustic, accelerometric, and temperature sensors. Developed through Lean process analysis and co-design workshops, REMEDY prioritizes multimorbidity management, multiparametric data fusion, workflow integration, and sustained patient engagement.