Abstract
Bioimpedance, or the electrical impedance of biological tissues, describes the passive electrical properties of these materials. To simplify bioimpedance datasets, fractional-order equivalent circuit presentations are often used, with the Cole-impedance model being one of the most widely used fractional-order circuits for this purpose. In this work, bioimpedance measurements from 10 kHz to 100 kHz were collected from participants biceps tissues immediately prior and immediately post completion of a fatiguing exercise protocol. The Cole-impedance parameters that best fit these datasets were determined using numerical optimization procedures, with relative errors of within approximately ± 0.5 % and ± 2 % for the simulated resistance and reactance compared to the experimental data. Comparison between the pre and post fatigue Cole-impedance parameters shows that the R ∞ , R 1 , and f p components exhibited statistically significant mean differences as a result of the fatigue induced changes in the study participants.
Highlights
Bioimpedance, or the electrical impedance of biological tissues, describes the passive electrical properties of these materials
While it has been previously shown that the bioimpedance at discrete frequencies (10 kHz, 50 kHz, and 100 kHz) of the biceps tissue does change due to exercise-induced fatigue [8] and that the biceps tissue bioimpedance can be well represented by the Cole-impedance model [23]; the changes in the Cole-impedance parameters that result from fatigue have not been deeply investigated
This study evaluates the parameters of the Cole-model equivalent electrical circuit that can represent bioimpedance datasets collected from the biceps tissues of participants immediately prior to and immediately post completion of a fatiguing exercise protocol; expanding on those analyses presented in [8,23]
Summary
Bioimpedance, or the electrical impedance of biological tissues, describes the passive electrical properties of these materials. The aim of collecting these measurements is to provide details regarding the electrochemical structures and processes within a tissue or material under study [1] These measurements are being used in a wide range of applications including: As a method to monitor hydration during hemodialysis [2], to detect changes resulting from muscle injury [3], assessing lympoedema [4], and to assess neuromuscular disorders [5]. Using equivalent electrical circuits can reduce a dataset from the potentially hundreds of datapoints to a smaller set (dependent on the number of circuit components in the model) This reduction is aimed at decreasing the complexity of tracking changes in the measured tissues.
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