Intra-breath measurements - supporting information of “Pattern recognition in intra-breath oscillometry measurements"

This measurement dataset is part of the supporting information for our article entitled “Pattern recognition in intra-breath oscillometry measurements”, which can be found through the references provided in the publication.
In addition to presenting the detailed methodology and results of our analysis, the article serves as a general guide for conducting machine learning (ML)-based classification using intra-breath oscillometry (IBOsc) data. It includes guidelines on signal preprocessing, feature extraction, artefact detection, aggregation strategies, and interpretable ML workflows.
About Intra-Breath Oscillometry (IBOsc):
The article introduces intra-breath oscillometry in more detail. Briefly, oscillometry is a non-invasive method for evaluating the mechanical properties of the respiratory system. The novel intra-breath variant (IBOsc) employs a single-frequency test signal (typically 10 Hz in adults) and computes respiratory impedance over short, overlapping time windows (approximately 0.1 seconds), capturing dynamic changes throughout the breathing cycle.
Dataset Structure:
The dataset includes multiple measurement visits of 871 patients (the article only included the firts visits).Each patient has a dedicated folder, which may contain multiple measurement files. The file naming structure adheres to the following convention: patietnID_measurementID_fileID.txt.inpx
Note: One visit may contain multiple repeated measures with different file IDs. All measurements were acquired using the tremoflo® C-100 device (THORASYS Thoracic Medical Systems Inc., Montreal, QC, Canada) in its research mode with 10 Hz single-frequency excitation.Subjects were seated, used a nose clip, and supported their cheeks with their hands, following the technical recommendations for routine oscillometry.Recordings lasted 20–30 seconds, capturing several full breathing cycles.The pressure and flow signals were sampled at 256 Hz and exported using the manufacturer’s software.labels.csv file contains metadata for the dataset. This file includes an index of the patients, the number of measurement files available for each patient, and their corresponding diagnostic label: healthy, COPD, or ILD.Data Content:
Each column in the .txt.inpx data files is explained in the article:Time (second): Timestamps for each sample.Vol (liter): Volume calculated from the flow signal.Pcyl (cmH₂O): Measured pressure.Flow (L/s): Respiratory flow signal.The paper provides step-by-step instructions on how to process these signals to compute the mechanical impedance of the respiratory system (Zrs) and offers explanations for all signal components involved.