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Updated: Feb 13, 2026

In Situ Lithiated Reference Electrode: Four Electrode Design for In-operando Impedance Spectroscopy
Published on: September 12, 2018
Forty years of reference values for respiratory system impedance in adults: 1977-2017
Or Kalchiem-Dekel1, Stella E Hines2
1Division of Pulmonary and Critical Care Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Objective:
To provide an evidence-based review of published data regarding normal range reference values and prediction equations for measurements of respiratory impedance using forced oscillation technique (FOT) and impulse oscillometry (IOs) in adults.
Methods:
A non-language-restricted search was performed using forced oscillation technique and impulse oscillometry as primary terms. Original research studies reporting respiratory system impedance reference values or prediction equations based on cohorts of ≥100 healthy adults were included. Publications cited in identified studies were also considered for inclusion.
Results:
Of 882 publications identified, 34 studies were included: 14 studies of FOT, 19 studies of IOs, and one study of both techniques. Nineteen studies provided prediction equations. Most reports were from Europe (n = 20) and Asia (n = 12) and included relatively small cohorts (median = 264 subjects). Across publications, there was marked variability in performance and technique of impedance measurements. Height and sex emerged as major contributors to available prediction equations. The contribution of weight was more pronounced at the obese end of the weight spectrum. The contribution of age was less clear, and elderly were largely under-represented. Ethnicity likely plays a role, but was under-reported in currently available literature. Inclusion of current and former smokers in some studies further confound the results.
Conclusions:
Currently available literature providing reference values and prediction equations for respiratory impedance measurements in adults is limited. Until larger-scale standardized studies are available, the choice of prediction equations should be based on datasets that best represent the target patient population and modality in use within each pulmonary physiology laboratory.
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