Classification of intra-breath oscillometry (IB-OSC) patterns for phenotyping paediatric respiratory disease

Oscillometry (OSC) is a sensitive technique for measuring respiratory system mechanics and is performed by superimposing a pressure signal over tidal breathing. Conventional OSC is measured using a signal containing multiple frequences and averaged across multiple acceptable breaths. This does not account for flow or volume dependent changes apparent during breathing. Our novel adaptation, IB-OSC, allows for continuous tracking across the breathing cycle using a single frequency and offers a more mechanism-oriented and granular view of respiratory function. AI-based classification of intra-breath patterns, in patients with COPD, reveals subtle changes in respiratory function that are otherwise missed when using conventional OSC. This project aims to explore different IB-OSC patterns in data collected from health children and children with respiratory conditions (particularly asthma and cystic fibrosis) and identify disease-specific mechanical patterns. 

For more information about this project, please contact Dr Tamara Blake