Abstract
Monitoring of nasal airflow and conductance provides crucial insights into the variable nature of the nasal resistance, nasal cycle, and ventilation. We have previously shown that tracking of pressure swings at the entrance of each nasal passage by a dedicated catheter system allows bilateral monitoring of nasal airflow over several hours but requires complex linearization and calibration procedures. Side-selective nasal conductance is derived from linearized and calibrated bilateral nasal pressure swings and corresponding driving pressure, i.e., the transnasal pressure difference derived from an epipharyngeal catheter. Manual analysis of such recordings and computation of instantaneous conductance as the ratio of flow to driving pressure over several hours is extremely tedious, time consuming, and therefore not suitable for routine practice. To address this point, we developed and validated a software for automatic processing of nasal and epipharyngeal pressure recordings as a convenient tool for studying the nasal ventilation. The software applies an eight-parameter logistic model to transform nasal pressure swings into side-selective estimates of airflow that are calibrated and further processed along with epipharyngeal pressure to compute bilateral nasal conductance over consecutive, user-selectable time-segments. Essential processing steps include (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. Among four evaluated algorithms for calculation of nasal conductance, the derivative of the airflow-pressure curve according to the mean value theorem agreed closest with the gold standard, i.e., the conductance derived from airflow measured by a pneumotachograph attached to an oral-nasal mask and transnasal pressure. In combination with the nasal catheter system, our novel software represents a valuable tool for use in clinical practice and research to conveniently investigate nasal ventilation and its changes occurring spontaneously or in response to various exposures and therapeutic interventions.
Highlights
Impaired nasal breathing caused by nasal obstruction compromises the quality of life during daytime and sleep (Craig et al, 1998)
An ideal diagnostic method for evaluation of nasal ventilation would allow to study the awake or asleep patient over prolonged time periods to capture the variability and side predominance of nasal ventilation. Such a technique would consist of two components: (i) an elaborate measurement instrumentation being unobtrusive, bilateral, patient unresponsive, of minimal instrumentation, applicable during sleep, and suitable for continuous recording, and (ii) an automated signal processing and analysis program capable of analyzing nasal breathing data recorded over several hours with high accuracy and temporal resolution delivering characteristic descriptors of nasal ventilation such as sideselective and total nasal conductance (Gn) and airflow
Our signal processing program for automatic, continuous transformation of bilateral pressure into airflow and conductance comprises two modules: the first module calibrates side-selective nasal pressure with airflow; the second module carries out the actual processing of bilateral nasal pressure recordings into airflow and conductance according to the calibration data generated by the first module
Summary
Impaired nasal breathing caused by nasal obstruction compromises the quality of life during daytime and sleep (Craig et al, 1998). An ideal diagnostic method for evaluation of nasal ventilation would allow to study the awake or asleep patient over prolonged time periods to capture the variability and side predominance of nasal ventilation. Such a technique would consist of two components: (i) an elaborate measurement instrumentation being unobtrusive, bilateral, patient unresponsive, of minimal instrumentation, applicable during sleep, and suitable for continuous recording, and (ii) an automated signal processing and analysis program capable of analyzing nasal breathing data recorded over several hours (e.g., overnight) with high accuracy and temporal resolution delivering characteristic descriptors of nasal ventilation such as sideselective and total nasal conductance (Gn) and airflow. Because processing of large recordings from overnight measurements (a recording time of 6 h at a frequency of 50 Hz results in 106 data points) inevitably precludes manual editing and evaluation, automated computer algorithms have to be used for data processing and analysis
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