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Analytical Model for Blood Glucose Detection Using Electrical Impedance Spectroscopy.
Pedro, Bruna Gabriela; Marcôndes, David William Cordeiro; Bertemes-Filho, Pedro.
Afiliação
  • Pedro BG; Departamento de Engenharia Elétrica, Universidade do Estado de Santa Catarina, Joinville 89219-710, Santa Catarina, Brazil.
  • Marcôndes DWC; Departamento de Engenharia Elétrica, Universidade do Estado de Santa Catarina, Joinville 89219-710, Santa Catarina, Brazil.
  • Bertemes-Filho P; Departamento de Engenharia Elétrica, Universidade do Estado de Santa Catarina, Joinville 89219-710, Santa Catarina, Brazil.
Sensors (Basel) ; 20(23)2020 Dec 04.
Article em En | MEDLINE | ID: mdl-33291529
Pathogens and adulterants in human feeding consumables can be readily identified according to their electrical properties. Electrical bioimpedance analysis (BIA) has been widely used for body contents characterization, such as blood, urine, lactate, and sweat. If the concentration of glucose in blood alters the electrical properties of the blood medium, then the impedance spectrum obtained by BIA can be used to measure glycemia. For some applications, artificial neural networks allow the correlation of these parameters both impedance and concentration of glucose by means of symbolic and statistical rules. According to our literature review, there is not any physical model that allows the interpretation of the relationship between blood's electrical properties from impedance spectra and the concentration of glucose in blood plasma. This article proposes a simplified physical model for blood electrical conductivity as a function of concentration of glucose, based on Bruggeman's effective medium theory. The equations of this model were obtained considering an insulating phase distribution diffused in a conductive matrix, in which red blood cells are represented by macroscopic insulating nuclei and glucose molecules by microscopic insulating particles. The impedance spectrum for different glucose concentrations (4.0 to 6.8 mmol/L) in a blood sample, published by Kamat Bagul (2014), were compared to the proposed model. The results showed a significant correlation with the experimental data, showing a maximum error of 5.2%. The proposed model might be useful in the design of noninvasive blood glucose monitoring systems.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Glicemia / Automonitorização da Glicemia / Espectroscopia Dielétrica Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Glicemia / Automonitorização da Glicemia / Espectroscopia Dielétrica Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça