Electrical Bioimpedance Sensing-Based Proximity Distance Estimation for Needle Interventions: Two-Layer Model and Validation

Needle-based interventions are routine in clinical practice, yet clinicians lack reliable, precise, real-time estimates of the tip-to-target distance—–a key determinant of safety and efficiency. To bridge this critical clinical gap, physics-based models that maps electrical bio-impedance (EBI) measurements to the absolute tip-to-target distance by leveraging tissue-intrinsic electrical properties encoded in EBI are presented in this work. A tripolar electrode configuration is adopted to ensure tool-independence and broad compatibility across instruments and anatomical sites. The optimal layout of electrode radius, inter-electrode spacing, and placement was identified through a systematic parametric study. The model was validated across finite-element simulations, saline solution experiments, andex vivolayered tissue. In all settings, proximity distance estimates were accurate and robust across different insertion angles. In simulation, it achieved 0.55 mm RMSE/1.06 mm MAE when the target layer was less conductive than the first layer and 0.40 mm RMSE/1.21 mm MAE when it was more conductive. In saline, four insertion angles yielded millimeter errors with no angle dependence. Inex vivolayered tissue, accuracy remained near the millimeter level across angles (RMSE 1.00–1.13 mm and MAE 1.30–1.58 mm), which is slightly lower than saline yet consistent across orientations. Together, these results establish a general, instrument-agnostic framework for absolute proximity distance sensing during needle interventions with the potential to enhance safety and efficiency in minimally invasive procedures. Furthermore, by first focusing on a two-layer model, this work provides a clear pathway to multi-layer tissue modeling and broader anatomical generalization.