Parametric Modeling of Human Wrist for Bioimpedance-Based Physiological Sensing

Bioimpedance is a powerful modality to continuously and non-invasively monitor cardiovascular and respiratory health parameters through the wearable operation. However, for bioimpedance sensors to be utilized in medical-grade settings, the reliability and robustness of the system should be improved. Previous studies provide limited fundamental analyses of the factors involved in the system that impact the sensitivity and the specificity of the modality in capturing the hemodynamics. This study provides a parametric model of the human wrist that involves different tissue layers (i.e., skin, fat, artery, muscle, bone) with complex dielectric properties built based on the human wrist anatomy. We run a frequency domain electrical field simulation using finite element analysis to map electric current distribution within the wrist to find the optimum operating frequency and electrode placement that provide the highest sensitivity and specificity to the blood flow. Our results suggest using an operating frequency between 10-100 kHz range with minimal electrode separation to capture the pulsatile activity with high accuracy.