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• W2758362241 endingPage "191" @default.
• W2758362241 startingPage "180" @default.
• W2758362241 abstract "The 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." @default.
• W2758362241 created "2017-10-06" @default.
• W2758362241 creator A5019777536 @default.
• W2758362241 creator A5079865418 @default.
• W2758362241 date "2018-02-01" @default.
• W2758362241 modified "2023-09-23" @default.
• W2758362241 title "Fractional models in electrical impedance spectroscopy data for glucose detection" @default.
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• W2758362241 doi "https://doi.org/10.1016/j.bspc.2017.09.017" @default.
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