Parametric Analysis of Bioimpedance Spectroscopy Measurement Data for a Simulated Human Limb
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Bioelectrical impedance analysis or bioimpedance analysis (BIA) is a non-invasive procedure originating in the early 1930s and 1940s that involves the measurement of the electrical impedance of a region of tissue. Bioimpedance measurements provide information about the physical and electrochemical processes in the tissue region and hence can be used for monitoring physiological properties and variations. For example, BIA is commonly employed to estimate body fat or water composition as a measure of general health. BIA has been implemented in diagnostic techniques such as electrical impedance cardiography (ICG) for estimating cardiac output, electrical impedance tomography (EIT) for imaging modality and electrical impedance spectroscopy (EIS) for multi-frequency analysis of materials with different electrical domains such as cellular membranes and tissues. Single frequency BIA (SFBIA) applications like ICG are more commonly used and provide an approximate response of the volume changes of blood within the thorax. However, the results are unreliable due to several assumptions related to tissue geometry and disregard the contribution of the surrounding tissues to the overall measurements. Herein, multi-frequency BIA (MFBIA) applications like EIS can be useful to provide an impedance spectrum containing information about the relaxation phenomenon of all the tissues. The aim of this research is to investigate the potential of MFBIA in determining the impedance response of each tissue through parametric electrical modelling, thereby helping to isolate the effects of one tissue from others. This thesis discusses a simulation perspective to determine the dielectric response of a human forearm section modelled with four layers – bone, fat, muscle and blood. The model, although assuming isotropic dielectric properties for each tissue, aims at simulating the dielectric response of the tissue layers within the major portion of β dispersion frequency range – 1 kHz to 1 MHz. The results established a Cole type behavior of the model within a frequency range of 10 kHz to 1 MHz. The simulation was followed by a pilot experimental investigation on a human forearm in two subjects. The results indicated a Cole type behavior for both the subjects within the measured frequency range of 1 kHz – 349 kHz. Both the simulation and the experimental measurements were modelled electrically to a single and multi-dispersion Cole equation to determine the Cole parameters for each tissue domain. The resultant model fit showed excellent correlation with the corresponding measured data and establishes this methodology to determine individual tissue response from overall MFBIA measurements.