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Updated: Jan 29, 2026

Conducting Respiratory Oscillometry in an Outpatient Setting
Published on: April 8, 2022
Impulse oscillometry and traditional pulmonary function testing: correlation, advances and clinical implications
Shihua Yao1, Linchong Huang1,2, Bingxia Chen1
1National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Abstract:
Impulse oscillometry system (IOS) is an effort-independent pulmonary function testing technique that assesses respiratory system mechanics during tidal breathing and has gained increasing interest as a complementary modality to traditional pulmonary function tests (PFTs), while its physiological relevance and clinical role alongside conventional tests remain incompletely defined. This narrative literature review synthesises evidence on the correlations between IOS parameters and traditional PFT indices, summarises clinical applications across major chronic respiratory diseases, and discusses emerging developments including artificial intelligence-based approaches; the review is based on studies published since 2010 that compare IOS with spirometry, body plethysmography, and diffusing capacity of the lung for carbon monoxide (DLCO) in chronic obstructive pulmonary disease (COPD), asthma, and interstitial lung disease (ILD). Correlation studies indicate that IOS resistance-related parameters are more closely associated with obstructive ventilatory impairment, particularly in COPD and asthma, whereas reactance-related parameters show stronger associations with restrictive ventilatory abnormalities, lung volumes, and diffusion impairment, especially in ILD. Across disease entities, R5-20 and resonant frequency consistently demonstrate higher sensitivity for detecting small airway dysfunction. Clinically, IOS provides value in assessing bronchodilator responsiveness, evaluating asthma control, detecting small airway involvement when spirometry is preserved, and monitoring exposure-related airway effects. Artificial intelligence-based models integrating multidimensional IOS data further highlight its potential in disease screening and classification. Overall, IOS provides complementary physiological and clinical information beyond traditional PFTs, and further large-scale, multicentre studies and methodological standardisation are needed to support its broader clinical implementation.
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