Extraction of Cole parameters from the electrical bioimpedance spectrum using stochastic optimization algorithms.

Fitting the measured bioimpedance spectroscopy (BIS) data to the Cole model and then extracting the Cole parameters is a common practice in BIS applications. The extracted Cole parameters then can be analysed as descriptors of tissue electrical properties. To have a better evaluation of physiologica...

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Publicado en:Medical & Biological Engineering & Computing Vol. 54; no. 4; pp. 643 - 652
Autores principales: Gholami-Boroujeny, Shiva, Bolic, Miodrag
Formato: algorithm equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Apr2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2016
      vid: 54
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      pub: Springer Nature
      place: New York, New York
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        atl: Extraction of Cole parameters from the electrical bioimpedance spectrum using stochastic optimization algorithms.
      aug:
        au:
          Gholami-Boroujeny, Shiva
          Bolic, Miodrag
        affil: School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa K1N 6N5 Canada
      sug:
        subj:
          Algorithms
          Electric Impedance Methods
          Statistics
          Databases
          Computer Simulation
          Female
          Electric Impedance
          Adult
          Regression
          Human
          Male
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Adult: 19-44 years
          Female
          Male
      ab: Fitting the measured bioimpedance spectroscopy (BIS) data to the Cole model and then extracting the Cole parameters is a common practice in BIS applications. The extracted Cole parameters then can be analysed as descriptors of tissue electrical properties. To have a better evaluation of physiological or pathological properties of biological tissue, accurate extraction of Cole parameters is of great importance. This paper proposes an improved Cole parameter extraction based on bacterial foraging optimization (BFO) algorithm. We employed simulated datasets to test the performance of the BFO fitting method regarding parameter extraction accuracy and noise sensitivity, and we compared the results with those of a least squares (LS) fitting method. The BFO method showed better robustness to the noise and higher accuracy in terms of extracted parameters. In addition, we applied our method to experimental data where bioimpedance measurements were obtained from forearm in three different positions of the arm. The goal of the experiment was to explore how robust Cole parameters are in classifying position of the arm for different people, and measured at different times. The extracted Cole parameters obtained by LS and BFO methods were applied to different classifiers. Two other evolutionary algorithms, GA and PSO were also used for comparison purpose. We showed that when the classifiers are fed with the extracted feature sets by BFO fitting method, higher accuracy is obtained both when applying on training data and test data.
      pubtype: Academic Journal
      doctype:
        algorithm
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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