Estimation of skin impedance models with experimental data and a proposed model for human skin impedance. Issue 5 (15th September 2020)

• Record Type: Journal Article
• Authors: Bora, Dhruba Jyoti; Dasgupta, Rajdeep
• Is Part Of: IET systems biology. Volume 14:Issue 5(2020)
• Page Start: 230
• Page End: 240
• Publication Date: 2020-09-15
• Subjects: genetic algorithms -- skin -- data analysis -- bioelectric phenomena -- medical computing -- electric impedance -- patient diagnosis; skin impedance models -- human skin impedance -- skin impedance analysis -- data analysis -- electrical models -- RC‐based model -- biological properties -- experimental skin impedance data -- fractional‐order CPE‐based model -- skin problems -- complex biological tissue -- higher‐order RC layered‐based model -- genetic algorithm -- diagnostic tools; Systems biology -- Periodicals; Cell physiology -- Periodicals; Biological systems -- Mathematical models -- Periodicals; Genetics -- Mathematical models -- Periodicals; Computational biology -- Periodicals; 573
• DOI: 10.1049/iet-syb.2020.0049
• Languages: English
• ISSNs: 1751-8849

Abstract

Abstract : The skin is a complex biological tissue whose impedance varies with frequency. The properties and structure of skin changes with the location on the body, age, geographical location and other factors. Considering these factors, skin impedance analysis is a sophisticated data analysis. However, despite all these variations, various researchers have always worked to develop an equivalent electrical model of the skin. The two most important categories of electrical models are RC‐based model and CPE‐based model which focus on the physiological stratification and biological properties of skin, respectively. In this work, experimental skin impedance data is acquired from ten sites on the body to find the fitting model. It is observed that a hybrid of fractional‐order CPE‐based model and higher‐order RC layered‐based model can provide the best fitting electrical model of skin. A new model is developed with this hybrid orders. Genetic algorithm is used for the extraction of parameter components. Least error of fitting has been observed for the proposed model as compared with the other models. This model can be used in correlating many skin problems and in the development of diagnostic tools. It will offer an additional supportive tool in‐vitro to the medical specialist.