L Nescolarde1, H Lukaski2, A De Lorenzo3, B de-Mateo-Silleras4, M P Redondo-Del-Río4, M A Camina-Martín4. 1. Department of Electronic Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain. 2. Department of Kinesiology and Public Health Education, Hyslop Sports Center, University of North Dakota, Grand Forks, ND, USA. 3. Department of Neuroscience, Division of Human Nutrition, University of Rome Tor Vergata, Rome, Italy. 4. Area of Nutrition and Food Science, Faculty of Medicine, Universidad de Valladolid, Valladolid, Spain.
Abstract
BACKGROUND/ OBJECTIVES: Bioelectrical impedance vector analysis (BIVA) is increasingly used in clinical research to assess soft tissue hydration. It is known that physical characteristics of electrodes, such as low intrinsic impedance, low electrode/skin contact impedance and type of gel, affect the reliability of noninvasive bioimpedance assessments. The aim of this study was to determine the effect of intrinsic impedance of electrode on the bioimpedance vector displacement in RXc graph. SUBJECTS/ METHODS: The intrinsic impedance is measured in nine pregelled disposable Ag/AgCl electrodes usually used for bioimpedance measures. The BIVA method is performed on 35 healthy volunteers using a 50 kHz phase-sensitive bioimpedance analyzer (BIA 101 Anniversary) with the lowest intrinsic impedance electrode and highest. The individual bioimpedance vector is plotted on the bivariate normal interval of reference population. The differences in the mean bioimpedance vectors obtained with each electrode are plotted, with their 95% confidence ellipses, on the dRXc graph. The paired one-sample Hotelling's T2-test is used to compare the differences of the mean bioimpedance vectors. RESULTS: We found large variability in intrinsic resistance (11-665 Ω) and reactance (0.25-2.5 Ω) values of the electrodes analyzed and significant displacement (P<0.05) of bioimpedance vector positions in healthy adults according to the paired one-sample Hotelling's T2-test. CONCLUSIONS: A robust study of all physical characteristics of commercial Ag/AgCl electrodes is necessary to reach consensus on pregelled Ag/AgCl electrodes valid for bioimpedance measurement. This information will enable BIVA users to avoid systemic errors when performing BIVA assessments, specifically when these measurements are used for clinical interpretations.
BACKGROUND/ OBJECTIVES: Bioelectrical impedance vector analysis (BIVA) is increasingly used in clinical research to assess soft tissue hydration. It is known that physical characteristics of electrodes, such as low intrinsic impedance, low electrode/skin contact impedance and type of gel, affect the reliability of noninvasive bioimpedance assessments. The aim of this study was to determine the effect of intrinsic impedance of electrode on the bioimpedance vector displacement in RXc graph. SUBJECTS/ METHODS: The intrinsic impedance is measured in nine pregelled disposable Ag/AgCl electrodes usually used for bioimpedance measures. The BIVA method is performed on 35 healthy volunteers using a 50 kHz phase-sensitive bioimpedance analyzer (BIA 101 Anniversary) with the lowest intrinsic impedance electrode and highest. The individual bioimpedance vector is plotted on the bivariate normal interval of reference population. The differences in the mean bioimpedance vectors obtained with each electrode are plotted, with their 95% confidence ellipses, on the dRXc graph. The paired one-sample Hotelling's T2-test is used to compare the differences of the mean bioimpedance vectors. RESULTS: We found large variability in intrinsic resistance (11-665 Ω) and reactance (0.25-2.5 Ω) values of the electrodes analyzed and significant displacement (P<0.05) of bioimpedance vector positions in healthy adults according to the paired one-sample Hotelling's T2-test. CONCLUSIONS: A robust study of all physical characteristics of commercial Ag/AgCl electrodes is necessary to reach consensus on pregelled Ag/AgCl electrodes valid for bioimpedance measurement. This information will enable BIVA users to avoid systemic errors when performing BIVA assessments, specifically when these measurements are used for clinical interpretations.
Authors: Carianne L'Abée; Petra H Poorts-Borger; Erna H G M Gorter; Antonio Piccoli; Ronald P Stolk; Pieter J J Sauer Journal: Clin Nutr Date: 2009-08-26 Impact factor: 7.324
Authors: Matthew T Stratton; Robert W Smith; Patrick S Harty; Christian Rodriguez; Baylor A Johnson; Jacob R Dellinger; Abegale D Williams; Sarah J White; Marqui L Benavides; Grant M Tinsley Journal: Eur J Clin Nutr Date: 2021-03-16 Impact factor: 4.016