Fractional models in electrical impedance spectroscopy data for glucose detection

摘要

Highlights•General fractional modeling identification for EIS applications.•Broadband periodic excitation signals to estimate and assess impedance measurements.•Methodology applied on different matrix solutions to discriminate glucose content.•Comparison of the proposed method with integer and circuits methodologies.•Fractional models are a feasible alternative to interpret the impedance of biological solutions.AbstractThe article presents a methodology to discriminate glucose levels using electrical impedance spectroscopy technology. The method is based on an adequate estimation and assessment of the impedance data followed by identification of a general rational fractional model. The methodology is illustrated on a group of saline–protein–glucose solutions at physiological concentrations, and shows the ability of the fractional models to discriminate glucose levels. The method exhibit significant differences in the zero position of the fractional model for different glucose concentrations allowing discriminate the glucose effect on the impedance data along different matrix solutions. The results based on fractional model method are compared with classical circuit models and rational integer models. Even when the different methodologies perceive variations in the impedance data given glucose alterations, the fractional models present low uncertainty allowing discriminating small glucose alterations in the physiological range.