Cargando…

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...

Descripción completa

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
_version_ 1785014611966164992
author Simić, Mitar
Freeborn, Todd J.
Šekara, Tomislav B.
Stavrakis, Adrian K.
Jeoti, Varun
Stojanović, Goran M.
author_facet Simić, Mitar
Freeborn, Todd J.
Šekara, Tomislav B.
Stavrakis, Adrian K.
Jeoti, Varun
Stojanović, Goran M.
author_sort Simić, Mitar
collection PubMed
description 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.
format Online
Article
Text
id pubmed-10050187
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-100501872023-03-30 A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware Simić, Mitar Freeborn, Todd J. Šekara, Tomislav B. Stavrakis, Adrian K. Jeoti, Varun Stojanović, Goran M. Sci Rep Article 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. Nature Publishing Group UK 2023-03-28 /pmc/articles/PMC10050187/ /pubmed/36977800 http://dx.doi.org/10.1038/s41598-023-31860-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Simić, Mitar
Freeborn, Todd J.
Šekara, Tomislav B.
Stavrakis, Adrian K.
Jeoti, Varun
Stojanović, Goran M.
A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware
title A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware
title_full A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware
title_fullStr A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware
title_full_unstemmed A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware
title_short A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware
title_sort novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware
topic Article
url 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
work_keys_str_mv AT simicmitar anovelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT freeborntoddj anovelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT sekaratomislavb anovelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT stavrakisadriank anovelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT jeotivarun anovelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT stojanovicgoranm anovelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT simicmitar novelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT freeborntoddj novelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT sekaratomislavb novelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT stavrakisadriank novelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT jeotivarun novelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware
AT stojanovicgoranm novelmethodforinsituextractingbioimpedancemodelparametersoptimizedforembeddedhardware