A novel approach for parameter estimation of Fricke-Morse model using differential impedance analysis

Abstract

In this paper we presented a new approach for parameter estimation of Fricke-Morse model (2R-1C circuit) of biological cell. Proposed method is based on Differential Impedance Analysis and it was applied in parameter estimation of five electrical bioimpedances: Total Body Composition, Trunk-Trunk, Arm-Arm, Leg-Leg and Respiration Rate. The proposed method has been evaluated regarding the influence of the number of measurement frequencies on the overall numerical accuracy and processing time. Obtained results are compared with Complex Non Linear Least Squares data fitting and it was showed that presented approach is significantly faster (ratio of processing times depends on the number of measurement frequencies). Additional advantage of the proposed method is very low computation complexity (it is not iterative) so it can be easily implemented in portable and autonomous low-cost microcontroller-based systems for bioimpedance measurement and parameter estimation of the Fricke-Morse model in real-time.