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Updated: Feb 25, 2026
Conducting Respiratory Oscillometry in an Outpatient Setting
Published on: April 8, 2022
Impact of breathing frequency on respiratory oscillometry measurements: a randomised cross-over and observational
Ben Knox-Brown1,2, Olga Carozzo3, Karl P Sylvester3,2
1Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK benjamin.knox-brown@nhs.net.
Introduction:
The impact of breathing frequency on respiratory oscillometry measurements is unknown. We aimed to investigate the impact of different breathing frequencies in patients with asthma.
Method:
We recruited patients from the severe asthma clinic at Cambridge University Hospitals. Using a randomised-crossover design, participants performed the forced oscillation technique at three different breathing frequencies (15, 30, 40 bpm) in a randomised order for each participant. A metronome was used to ensure the correct breathing frequency. Analysis of variance (ANOVA) and Friedman tests were utilised to assess the significance of any differences across the breathing frequencies. We then leveraged cross-sectional data from asthma patients who performed respiratory oscillometry and investigated the determinants of self-selected breathing frequency using multivariable linear regression.
Results:
We recruited 59 patients. Mean age 54.1 years, 58% female, median forced expiratory volume in 1 s (FEV1)/FVC z-score -2.56 (-3.26 to -1.96). As breathing frequency increased from 15 bpm to 40 bpm, there was a significant reduction (-8.6%, p<0.001) in total airway resistance (Rrs at 5 Hz), which was not mediated by changes in tidal volume or flow rate. There was also a significant reduction (-14.9%, p<0.001) in Delta R5-R19, and an increase (+10.9%, p=0.081) in reactance (Xrs at 5 Hz). At higher breathing frequencies, 5% of study participants were reclassified as having respiratory oscillometry measurements within normal limits. Data from 796 asthma patients were extracted for the cross-sectional analysis. The median (range) self-selected breathing frequency was 16.55 bpm (8.0, 42.0). Demographic data and lung function explained 23.5% of the variation in breathing frequency.
Conclusion:
Higher breathing frequencies significantly reduce total Rrs . When performing respiratory oscillometry, breathing frequency should be controlled at approximately 15 bpm to reduce risk of misclassification.
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