Digital Twin Driven Electrode Optimization for Wearable Bladder Monitoring Via Bioimpedance

Monitoring fluid intake and output for congestive heart failure (CHF) patients is an essential tool to prevent fluid overload, a principal cause of hospital admissions. Addressing this, bladder volume measurement systems utilizing bioimpedance and electrical impedance tomography have been proposed, with limited exploration of continuous monitoring within a wearable design. Advancing this format, we developed a conductivity digital twin from radiological data, where we performed exhaustive simulations to optimize electrode sensitivity on an individual basis. Our optimized placement demonstrated an efficient proof-of-concept volume estimation that required as few as seven measurement frames while maintaining low errors (CI 95% -1.11% to 1.00%) for volumes ≥100 mL. Additionally, we quantify the impact of ascites, a common confounding condition in CHF, on the bioimpedance signal. By improving monitoring technology, we aim to reduce CHF mortality by empowering patients and clinicians with a more thorough understanding of fluid status.