Digital twin driven electrode optimization for wearable bladder monitoring via bioimpedance.

Abstract

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.