Application of nature inspired optimization algorithms in bioimpedance spectroscopy: simulation and experiment

Abhishek Mallick; Atanu Mondal; Somnath Bhattacharjee; Arijit Roy; Abhishek Mallick; Atanu Mondal; Somnath Bhattacharjee; Arijit Roy

doi:10.3934/biophy.2023010

AIMS Biophysics

2023, Volume 10, Issue 2: 132-172. doi: 10.3934/biophy.2023010

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Research article Special Issues

Application of nature inspired optimization algorithms in bioimpedance spectroscopy: simulation and experiment

Department of Electronics, West Bengal State University, Barasat, Kolkata, India 700126

Received: 24 November 2022 Revised: 07 March 2023 Accepted: 21 March 2023 Published: 07 April 2023

Accurate extraction of Cole parameters for applications in bioimpedance spectroscopy (BIS) is challenging. Precise estimation of Cole parameters from measured bioimpedance data is crucial, since the physiological state of any biological tissue or body is described in terms of Cole parameters. To extract Cole parameters from measured bioimpedance data, the conventional gradient-based non-linear least square (NLS) optimization algorithm is found to be significantly inaccurate. In this work, we have presented a robust methodology to establish an accurate process to estimate Cole parameters and relaxation time from measured BIS data. Six nature inspired algorithms, along with NLS are implemented and studied. Experiments are conducted to obtain BIS data and analysis of variation (ANOVA) is performed. The Cuckoo Search (CS) algorithm achieved a better fitment result and is also able to extract the Cole parameters most accurately among all the algorithms under consideration. The ANOVA result shows that CS algorithm achieved a higher confidence rate. In addition, the CS algorithm requires less sample size compared to other algorithms for distinguishing the change in physical properties of a biological body.
- algorithm,
- ANOVA,
- bioimpedance,
- Cole parameters,
- nature-inspired,
- optimization
Citation: Abhishek Mallick, Atanu Mondal, Somnath Bhattacharjee, Arijit Roy. Application of nature inspired optimization algorithms in bioimpedance spectroscopy: simulation and experiment[J]. AIMS Biophysics, 2023, 10(2): 132-172. doi: 10.3934/biophy.2023010

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Abstract

Accurate extraction of Cole parameters for applications in bioimpedance spectroscopy (BIS) is challenging. Precise estimation of Cole parameters from measured bioimpedance data is crucial, since the physiological state of any biological tissue or body is described in terms of Cole parameters. To extract Cole parameters from measured bioimpedance data, the conventional gradient-based non-linear least square (NLS) optimization algorithm is found to be significantly inaccurate. In this work, we have presented a robust methodology to establish an accurate process to estimate Cole parameters and relaxation time from measured BIS data. Six nature inspired algorithms, along with NLS are implemented and studied. Experiments are conducted to obtain BIS data and analysis of variation (ANOVA) is performed. The Cuckoo Search (CS) algorithm achieved a better fitment result and is also able to extract the Cole parameters most accurately among all the algorithms under consideration. The ANOVA result shows that CS algorithm achieved a higher confidence rate. In addition, the CS algorithm requires less sample size compared to other algorithms for distinguishing the change in physical properties of a biological body.

Acknowledgments

The first author would like to thank to Department of Science and Technology, Govt. of India for providing research fellowship under “DST Inspire Fellowship (IF 170260)” scheme.

Conflict of interest

The authors declare no conflict of interest.

Author contributions

First author: Played role in experimentation. Second author: Played major role in execution, programming in Python, ANOVA, data fitting and documentation. Third author: Assisting in execution and documentation. Fourth author: Played role in idea generation, research planning and supervision.

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