用实验数据估计皮肤阻抗模型,并提出一种人体皮肤阻抗模型

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2020-09-15 DOI:10.1049/iet-syb.2020.0049
Dhruba Jyoti Bora, Rajdeep Dasgupta
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引用次数: 11

摘要

皮肤是一种复杂的生物组织,其阻抗随频率而变化。皮肤的性质和结构随着身体的位置、年龄、地理位置等因素而变化。考虑到这些因素,皮肤阻抗分析是一项复杂的数据分析。然而,尽管有这些变化,不同的研究人员一直在努力开发一个等效的皮肤电模型。两类最重要的电模型是基于rc的模型和基于cpe的模型,它们分别关注皮肤的生理分层和生物学特性。在这项工作中,我们从身体的十个部位获取皮肤阻抗的实验数据来寻找拟合模型。结果表明,分数阶cpe模型和高阶RC分层模型的混合模型可以提供最适合皮肤的电模型。利用这种混合订单开发了一种新的模型。采用遗传算法对参数分量进行提取。与其他模型相比,该模型的拟合误差最小。该模型可用于许多皮肤问题的关联和诊断工具的开发。它将为医学专家提供额外的体外辅助工具。
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Estimation of skin impedance models with experimental data and a proposed model for human skin impedance

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.

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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
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