A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware
Abstract 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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-03-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-31860-w |
| _version_ | 1797853780149010432 |
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| author | Mitar Simić Todd J. Freeborn Tomislav B. Šekara Adrian K. Stavrakis Varun Jeoti Goran M. Stojanović |
| author_facet | Mitar Simić Todd J. Freeborn Tomislav B. Šekara Adrian K. Stavrakis Varun Jeoti Goran M. Stojanović |
| author_sort | Mitar Simić |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-09T19:56:22Z |
| format | Article |
| id | doaj.art-515144f82fe44a6dbde65df44f96f866 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-09T19:56:22Z |
| publishDate | 2023-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-515144f82fe44a6dbde65df44f96f8662023-04-03T05:27:57ZengNature PortfolioScientific Reports2045-23222023-03-0113111210.1038/s41598-023-31860-wA novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardwareMitar Simić0Todd J. Freeborn1Tomislav B. Šekara2Adrian K. Stavrakis3Varun Jeoti4Goran M. Stojanović5Faculty of Technical Sciences, University of Novi SadDepartment of Electrical and Computer Engineering, The University of AlabamaSchool of Electrical Engineering, University of BelgradeFaculty of Technical Sciences, University of Novi SadFaculty of Technical Sciences, University of Novi SadFaculty of Technical Sciences, University of Novi SadAbstract 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.https://doi.org/10.1038/s41598-023-31860-w |
| spellingShingle | Mitar Simić Todd J. Freeborn Tomislav B. Šekara Adrian K. Stavrakis Varun Jeoti Goran M. Stojanović A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware Scientific Reports |
| 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 |
| url | https://doi.org/10.1038/s41598-023-31860-w |
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