Original Research ARTICLE
Automatic Processing of Nasal Pressure Recordings to Derive Continuous Side-Selective Nasal Airflow and Conductance
- 1Respiratory Medicine, UniversitätsSpital Zürich, Switzerland
The continuous monitoring of nasal airflow and conductance reveals crucial insight into the variable nature of nasal resistance, nasal cycle, breathing pattern, and ventilation. Unobtrusive tracking of side-selective nasal pressure by a specially designed catheter system at the entrance of each nasal passage can serve as a means for monitoring side-selective nasal airflow over several hours if a suitable linearization procedure and calibration are applied. Side-selective nasal conductance is obtained as calculated ratio of the derived nasal airflow and simultaneously recorded epipharyngeal pressure. Manual analysis of nasal flow and epipharyngeal pressure recordings and computation of instantaneous conductance over several hours is extremely tedious, time consuming and therefore not practicable. To address this point, we describe the signal processing principles and validation of a computer program, which performs automatic calibration using an 8-parameter logistic model and processing of side-selective nasal pressure recordings into airflow and, in combination with epipharyngeal pressure, conductance. Pressure recordings may be subdivided into user-defined consecutive time-segments (e.g. 2 min intervals) and processed by 1) offset correction, 2) low-pass filtering, 3) cross-correlation, 4) cutting of signals into individual breaths, 5) normalization, 6) ensemble averaging to obtain a mean pressure signal for each nasal side, 7) derivation of airflow, conductance and further variables. Comparison of four algorithms for the calculation of nasal conductance revealed that the derivative of the airflow-pressure curve according to the mean value theorem gave good agreement with the gold standard, independent flow-meter-derived conductance, according to a Bland-Altman analysis. In combination with the nasal catheter system, our nasal signal processing software represents a valuable tool for the convenient evaluation of nasal physiology and of disturbances of nasal ventilation over time.
Keywords: Nasal airflow analysis, Nasal resistance, Monitoring, automatic, Rhinomanometry, Nasal physiology, Nasal pressure signal, Nasal air passage obstruction, nasal airflow dynamics
Received: 22 Jul 2018;
Accepted: 05 Dec 2018.
Edited by:Ahsan H. Khandoker, Khalifa University, United Arab Emirates
Reviewed by:Chin Moi Chow, University of Sydney, Australia
F Javier Belda, University of Valencia, Spain
Copyright: © 2018 Urner, Kohler and Bloch. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Konrad E. Bloch, UniversitätsSpital Zürich, Respiratory Medicine, Zurich, Switzerland, firstname.lastname@example.org