Gastric Electrical Impedance Tomography (gEIT) Based on a 3D Jacobian Matrix and Dual-Step Fuzzy Clustering Post-Processing

We propose a gastric electrical impedance tomography ( {g} EIT) scheme that uses a 3D full Jacobian matrix ^\ast \text{J} and dual-step fuzzy clustering post-processing to automatically extract the gastric content volume {V} . {g} EIT has two stages: (i) computation of the full 3D Jacobian matrix ^\ast \text{J} , including all combinations of the current injection pattern {I} and the impedance measurement {Z} , in order to reconstruct the volumetric abdomen conductivity \sigma ; and (ii) clustering of the gastric composition ^{k} \sigma (gastric wall {k}={1} , gastric content {k}={2} ) using dual-step fuzzy clustering post-processing, in order to automatically extract the volumetric gastric conductivity ^{k} \sigma . Our {g} EIT scheme is qualitatively evaluated using realistic abdomen phantoms representing three gastric accommodation phases, based on three different values for the gastric content volume filled with liquid meal: (A) {V}_{A} = {100} mL; (B) {V}_{B} = {300} mL; and (C) {V}_{C} = {600} mL, for two abdomen shapes (a normal abdomen {S} and a fatty abdomen {L} ) through both simulation and experimental studies. The results show that