Simulation of Impedance Measurements at Human Forearm Within 1 KHz to 2 MHz

This work presents a simulation analysis of the bioimpedance measurements at human forearm. The Ansys® High Frequency Structure Simulator (HFSS) has been used to analyze the electrical response of a section of human forearm with three domains of di-electric behavior- fat, muscle and artery (blood). The impedance values were calculated as the ratio of the output voltage at the electrodes to the applied known current (1mA). A model was developed and was simulated for impedance values obtained within a frequency range of 1 kHz to 2MHz. The measurements were done at three instances of radial artery diameter. The maximum resistance and reactance values were calculated as 445Ω and 178.5Ω, 356Ω and 138Ω, and 368Ω and 144.3Ω for diameters 2.3mm, 2.35mm, and 2.4mm respectively. The set of impedance values obtained followed Cole-plot trend. The results obtained were found to be in excellent agreement with the Cole theory. The set of values obtained at three different diameters reflected the effect of blood flow on impedance values

Bioimpedance as a predictor of survival in renal failure and associated comorbidities.

Background: Renal failure requiring dialysis is associated with a high mortality. One of the contributing causes is overhydration. Overhydration can be assessed by bioimpedance analysis (BIA)– the non-invasive electrical measure of small current through the tissues that estimates the proportion of fluid that is intracellular water (ICW, typically muscle which is healthy) and extracellular (ECW, which in excess causes tissue oedema and is potentially dangerous). Several studies indicate that a extracellular water to total body water (TBW) ratio is associated with increased risk of death in dialysis patients but it is not clear if this is independent of other risk factors for death, namely comorbidity. Aims and objectives: To establish the prognostic value of BIA in the prediction of survival on dialysis in the context of other known predictors of survival or hospitalisation. With further analysis of the applicability of the same scenario to heart failure patients. Methodology: To conduct a systematic review using a standardised approach including a prespecified research question, search terms and criteria for study inclusion. With independent selection for inclusion in the study and quality appraisal by multiple authors with different backgrounds and experience. Results: 2701 studies identified by literature search, plus an additional 4 through reference checking. 38 papers included in final analysis, 4 of which were regarding heart failure cohorts. Analysis of the research shows that BIA is an independent predictor of mortality. Conclusion: BIA shown to be an independent predictor of mortality in dialysis patients, further research needed to extrapolate to heart failure (HF) populations