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A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware

A novel method for embedded hardware-based parameter estimation of the Cole model of bioimpedance is developed and presented. The model parameters R(∞), R(1) and C are estimated using the derived set of equations based on measured values of real (R) and imaginary part (X) of bioimpedance, as well as...

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Detalles Bibliográficos
Autores principales: Simić, Mitar, Freeborn, Todd J., Šekara, Tomislav B., Stavrakis, Adrian K., Jeoti, Varun, Stojanović, Goran M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050187/
https://www.ncbi.nlm.nih.gov/pubmed/36977800
http://dx.doi.org/10.1038/s41598-023-31860-w
Descripción
Sumario:A novel method for embedded hardware-based parameter estimation of the Cole model of bioimpedance is developed and presented. The model parameters R(∞), R(1) and C are estimated using the derived set of equations based on measured values of real (R) and imaginary part (X) of bioimpedance, as well as the numerical approximation of the first derivative of quotient R/X with respect to angular frequency. The optimal value for parameter α is estimated using a brute force method. The estimation accuracy of the proposed method is very similar with the relevant work from the existing literature. Moreover, performance evaluation was performed using the MATLAB software installed on a laptop, as well as on the three embedded-hardware platforms (Arduino Mega2560, Raspberry Pi Pico and XIAO SAMD21). Obtained results showed that the used platforms can perform reliable bioimpedance processing with the same accuracy, while Raspberry Pi Pico is the fastest solution with the smallest energy consumption.