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  • 1.
    Buendía, Rubén
    et al.
    University of Borås, School of Engineering.
    Bogónez-Franco, Paco
    Nescolarde, Lexa
    Seoane, Fernando
    University of Borås, School of Engineering.
    Influence of electrode mismatch on Cole parameter estimation from Total Right Side Electrical Bioimpedance Spectroscopy measurements2012In: Medical Engineering and Physics, ISSN 1350-4533, E-ISSN 1873-4030, Vol. 34, no 7, p. 1024-1028Article in journal (Refereed)
    Abstract [en]

    Applications based on measurements of Electrical Bioimpedance (EBI) spectroscopy analysis, like assessment of body composition, have proliferated in the past years. Currently Body Composition Assessment (BCA) based in Bioimpedance Spectroscopy (BIS) analysis relays on an accurate estimation of the Cole parameters R0 and R∞. A recent study by Bogonez-Franco et al. has proposed electrode mismatch as source of remarkable artefacts in BIS measurements. Using Total Right Side BIS measurements from the aforementioned study, this work has focused on the influence of electrode mismatch on the estimation of R0 and R∞ using the Non-Linear Least Square curve fitting technique on the modulus of the impedance. The results show that electrode mismatch on the voltage sensing electrodes produces an overestimation of the impedance spectrum leading to a wrong estimation of the parameters R0 and R∞, and consequently obtaining values around 4% larger that the values obtained from BIS without electrode mismatch. The specific key factors behind electrode mismatch or its influence on the analysis of single and spectroscopy measurements have not been investigated yet, no compensation or correction technique is available to overcome the deviation produced on the EBI measurement. Since textile-enabled EBI applications using dry textrodes, i.e. textile electrodes with dry skin–electrode interfaces and potentially large values of electrode polarization impedance are more prone to produce electrode mismatch, the lack of a correction or compensation technique might hinder the proliferation of textile-enabled EBI applications for personalized healthcare monitoring.

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