Characterization of Impulse Oscillometric Measures of Respiratory Small Airway Function in Children

Abstract

Children suffering from asthma are often undiagnosed or misdiagnosed as their symptoms are similar to other respiratory conditions. Spirometry, the golden pulmonary function test used for asthma diagnosis, is often unsuitable for young children since it requires them to perform extreme inhalation and exhalation maneuvers. Impulse Oscillometry (IOS) is an effortless, child-friendly, sensitive, and reliable testing technique that could be used in the effective diagnosis of asthma. However, the IOS requires a deep understanding of the mechanical and/or equivalent electrical circuit models of the human respiratory system, which hinders its broad acceptance and utility in clinics. This paper presents a data characterization study based on the statistical assessment of the IOS parameters. The main focus is to investigate four different manifestations of pulmonary conditions in children due to peripheral obstruction: Asthma (A), Small Airway Impairment (SAI), Possible Small Airway Impairment (PSAI), and Normal (N). The objective of this investigation is to pave the way for the feature selection stage of our future computer-aided classification work to distinguish between lung dysfunction and healthy lung function in children by identifying those IOS parameters that are most sensitive to discriminate between the different respiratory conditions mentioned above. Our ultimate goal is to facilitate the interpretation of the impulse oscillometric test results and provide clinicians with a reliable and proven method for accurate classification of children's lung function for an early asthma detection, diagnosis, and control.